From a557a55b8bdd2923f1b4a9b3e4e0ff402cc05aeb Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=9B=BE=E8=81=AA?= <wucong.lyb@alibaba-inc.com>
Date: Tue, 20 Jun 2023 10:25:53 +0800
Subject: [PATCH 1/4] update funasr-wss-client funasr-wss-server

---
 .../runtime/websocket/funasr-wss-client.cpp   |  3 +-
 .../runtime/websocket/funasr-wss-server.cpp   | 84 +++++++++++++++++--
 2 files changed, 80 insertions(+), 7 deletions(-)

diff --git a/funasr/runtime/websocket/funasr-wss-client.cpp b/funasr/runtime/websocket/funasr-wss-client.cpp
index 8b59000fc..53301253c 100644
--- a/funasr/runtime/websocket/funasr-wss-client.cpp
+++ b/funasr/runtime/websocket/funasr-wss-client.cpp
@@ -277,13 +277,14 @@ class WebsocketClient {
 };
 
 int main(int argc, char* argv[]) {
+
     google::InitGoogleLogging(argv[0]);
     FLAGS_logtostderr = true;
 
     TCLAP::CmdLine cmd("funasr-ws-client", ' ', "1.0");
     TCLAP::ValueArg<std::string> server_ip_("", "server-ip", "server-ip", true,
                                            "127.0.0.1", "string");
-    TCLAP::ValueArg<std::string> port_("", "port", "port", true, "8889", "string");
+    TCLAP::ValueArg<std::string> port_("", "port", "port", true, "10095", "string");
     TCLAP::ValueArg<std::string> wav_path_("", "wav-path", 
         "the input could be: wav_path, e.g.: asr_example.wav; pcm_path, e.g.: asr_example.pcm; wav.scp, kaldi style wav list (wav_id \t wav_path)", 
         true, "", "string");
diff --git a/funasr/runtime/websocket/funasr-wss-server.cpp b/funasr/runtime/websocket/funasr-wss-server.cpp
index 5f2af5ce0..a6fa2e137 100644
--- a/funasr/runtime/websocket/funasr-wss-server.cpp
+++ b/funasr/runtime/websocket/funasr-wss-server.cpp
@@ -11,6 +11,7 @@
 //                    [--vad-quant <string>] [--vad-dir <string>] [--quantize
 //                    <string>] --model-dir <string> [--] [--version] [-h]
 #include "websocket-server.h"
+#include <unistd.h>
 
 using namespace std;
 void GetValue(TCLAP::ValueArg<std::string>& value_arg, string key,
@@ -20,10 +21,15 @@ void GetValue(TCLAP::ValueArg<std::string>& value_arg, string key,
 }
 int main(int argc, char* argv[]) {
   try {
+
     google::InitGoogleLogging(argv[0]);
     FLAGS_logtostderr = true;
 
     TCLAP::CmdLine cmd("funasr-ws-server", ' ', "1.0");
+    TCLAP::ValueArg<std::string> download_model_dir(
+        "", "download-model-dir",
+        "Download model from Modelscope to download_model_dir",
+        false, "", "string");
     TCLAP::ValueArg<std::string> model_dir(
         "", MODEL_DIR,
         "default: /workspace/models/asr, the asr model path, which contains model.onnx, config.yaml, am.mvn",
@@ -53,15 +59,15 @@ int main(int argc, char* argv[]) {
         "true, load the model of model_quant.onnx in punc_dir",
         false, "true", "string");
 
-    TCLAP::ValueArg<std::string> listen_ip("", "listen_ip", "listen_ip", false,
+    TCLAP::ValueArg<std::string> listen_ip("", "listen-ip", "listen ip", false,
                                            "0.0.0.0", "string");
-    TCLAP::ValueArg<int> port("", "port", "port", false, 8889, "int");
-    TCLAP::ValueArg<int> io_thread_num("", "io_thread_num", "io_thread_num",
+    TCLAP::ValueArg<int> port("", "port", "port", false, 10095, "int");
+    TCLAP::ValueArg<int> io_thread_num("", "io-thread-num", "io thread num",
                                        false, 8, "int");
     TCLAP::ValueArg<int> decoder_thread_num(
-        "", "decoder_thread_num", "decoder_thread_num", false, 8, "int");
-    TCLAP::ValueArg<int> model_thread_num("", "model_thread_num",
-                                          "model_thread_num", false, 1, "int");
+        "", "decoder-thread-num", "decoder thread num", false, 8, "int");
+    TCLAP::ValueArg<int> model_thread_num("", "model-thread-num",
+                                          "model thread num", false, 1, "int");
 
     TCLAP::ValueArg<std::string> certfile("", "certfile", 
         "default: ../../../ssl_key/server.crt, path of certficate for WSS connection. if it is empty, it will be in WS mode.", 
@@ -73,6 +79,7 @@ int main(int argc, char* argv[]) {
     cmd.add(certfile);
     cmd.add(keyfile);
 
+    cmd.add(download_model_dir);
     cmd.add(model_dir);
     cmd.add(quantize);
     cmd.add(vad_dir);
@@ -95,6 +102,71 @@ int main(int argc, char* argv[]) {
     GetValue(punc_dir, PUNC_DIR, model_path);
     GetValue(punc_quant, PUNC_QUANT, model_path);
 
+    // Download model form Modelscope
+    try{
+        std::string s_download_model_dir = download_model_dir.getValue();
+        if(download_model_dir.isSet() && !s_download_model_dir.empty()){
+            if (access(s_download_model_dir.c_str(), F_OK) != 0){
+                LOG(ERROR) << s_download_model_dir << " do not exists."; 
+                exit(-1);
+            }
+            std::string s_vad_path = model_path[VAD_DIR];
+            std::string s_asr_path = model_path[MODEL_DIR];
+            std::string s_punc_path = model_path[PUNC_DIR];
+            std::string python_cmd = "python -m funasr.export.export_model --type onnx --quantize True ";
+            if(vad_dir.isSet() && !s_vad_path.empty()){
+                std::string python_cmd_vad = python_cmd + " --model-name " + s_vad_path + " --export-dir " + s_download_model_dir;
+                LOG(INFO) << "Download model: " <<  s_vad_path << " from modelscope: ";
+                system(python_cmd_vad.c_str());
+                std::string down_vad_path = s_download_model_dir+"/"+s_vad_path;
+                std::string down_vad_model = s_download_model_dir+"/"+s_vad_path+"/model_quant.onnx";
+                if (access(down_vad_model.c_str(), F_OK) != 0){
+                  LOG(ERROR) << down_vad_model << " do not exists."; 
+                  exit(-1);
+                }else{
+                  model_path[VAD_DIR]=down_vad_path;
+                  LOG(INFO) << "Set " << VAD_DIR << " : " << model_path[VAD_DIR];
+                }
+            }else{
+              LOG(INFO) << "VAD model is not set, use default.";
+            }
+            if(model_dir.isSet() && !s_asr_path.empty()){
+                std::string python_cmd_asr = python_cmd + " --model-name " + s_asr_path + " --export-dir " + s_download_model_dir;
+                LOG(INFO) << "Download model: " <<  s_asr_path << " from modelscope: ";
+                system(python_cmd_asr.c_str());
+                std::string down_asr_path = s_download_model_dir+"/"+s_asr_path;
+                std::string down_asr_model = s_download_model_dir+"/"+s_asr_path+"/model_quant.onnx";
+                if (access(down_asr_model.c_str(), F_OK) != 0){
+                  LOG(ERROR) << down_asr_model << " do not exists."; 
+                  exit(-1);
+                }else{
+                  model_path[MODEL_DIR]=down_asr_path;
+                  LOG(INFO) << "Set " << MODEL_DIR << " : " << model_path[MODEL_DIR];
+                }
+            }else{
+              LOG(INFO) << "ASR model is not set, use default.";
+            }
+            if(punc_dir.isSet() && !s_punc_path.empty()){
+                std::string python_cmd_punc = python_cmd + " --model-name " + s_punc_path + " --export-dir " + s_download_model_dir;
+                LOG(INFO) << "Download model: " << s_punc_path << " from modelscope: ";
+                system(python_cmd_punc.c_str());
+                std::string down_punc_path = s_download_model_dir+"/"+s_punc_path;
+                std::string down_punc_model = s_download_model_dir+"/"+s_punc_path+"/model_quant.onnx";
+                if (access(down_punc_model.c_str(), F_OK) != 0){
+                  LOG(ERROR) << down_punc_model << " do not exists."; 
+                  exit(-1);
+                }else{
+                  model_path[PUNC_DIR]=down_punc_path;
+                  LOG(INFO) << "Set " << PUNC_DIR << " : " << model_path[PUNC_DIR];
+                }
+            }else{
+              LOG(INFO) << "PUNC model is not set, use default.";
+            }    
+        }
+    } catch (std::exception const& e) {
+        LOG(ERROR) << "Error: " << e.what();
+    }
+
     std::string s_listen_ip = listen_ip.getValue();
     int s_port = port.getValue();
     int s_io_thread_num = io_thread_num.getValue();

From 369f2ff8838569351c26d909407b497ab16d3bcf Mon Sep 17 00:00:00 2001
From: zhaomingwork <61895407+zhaomingwork@users.noreply.github.com>
Date: Tue, 20 Jun 2023 11:08:50 +0800
Subject: [PATCH 2/4] add html5 local access asr service directly (#654)

---
 funasr/runtime/html5/readme.md             |  14 +-
 funasr/runtime/html5/static/index.html     |  25 ++-
 funasr/runtime/html5/static/main.js        | 192 ++++++++++++++++++---
 funasr/runtime/html5/static/wsconnecter.js |   7 +-
 4 files changed, 207 insertions(+), 31 deletions(-)

diff --git a/funasr/runtime/html5/readme.md b/funasr/runtime/html5/readme.md
index 1e9031eec..0c1eba0ea 100644
--- a/funasr/runtime/html5/readme.md
+++ b/funasr/runtime/html5/readme.md
@@ -51,8 +51,18 @@ https://127.0.0.1:1337/static/index.html
 # https://30.220.136.139:1337/static/index.html
 ```
 
-### modify asr address in html according to your environment
-asr address in index.html must be wss
+### open browser to open html5 file directly without h5Server
+you can run html5 client by just clicking the index.html file directly in your computer.
+1) lauch asr service without ssl, it must be in ws mode as ssl protocol will prohibit such access.
+2) copy whole directory /funasr/runtime/html5/static to your computer
+3) open /funasr/runtime/html5/static/index.html by browser
+4) enter asr service ws address and connect
+
+
+```shell
+
+```
+ 
 
 
 ## Acknowledge
diff --git a/funasr/runtime/html5/static/index.html b/funasr/runtime/html5/static/index.html
index 99aa9b477..23d6fece3 100644
--- a/funasr/runtime/html5/static/index.html
+++ b/funasr/runtime/html5/static/index.html
@@ -21,14 +21,35 @@
 				<br>
 				<input id="wssip" type="text" style=" width: 100%;height:100%" value="wss://127.0.0.1:10095/"/>
 				<br>
+			<br>  
+			<div  style="border:2px solid #ccc;">
+				选择录音模式:<br/>
+    
+        <label><input name="recoder_mode" onclick="on_recoder_mode_change()" type="radio" value="mic" checked="true"/>麦克风 </label>&nbsp;&nbsp;
+        <label><input name="recoder_mode" onclick="on_recoder_mode_change()" type="radio" value="file" />文件 </label> 
+
+				</div>
+				
 				<br>
-				<div style="border:2px solid #ccc;">
+				 <div id="mic_mode_div" style="border:2px solid #ccc;display:block;">
 				选择asr模型模式:<br/>
+    
       <label><input name="asr_mode" type="radio" value="2pass" checked="true"/>2pass </label>&nbsp;&nbsp;
       <label><input name="asr_mode" type="radio" value="online" />online </label>&nbsp;&nbsp;
-      <label><input name="asr_mode" type="radio" value="offline" />offline </label> 
+      <label><input name="asr_mode" type="radio" value="offline" />offline </label>
+
+				</div>
+				
+				<div id="rec_mode_div" style="border:2px solid #ccc;display:none;">
+		 
+    
+		          <input type="file" id="upfile">
+
 				</div>
 				<br>
+		
+				
+			 
 				语音识别结果显示：
 				<br>
 				
diff --git a/funasr/runtime/html5/static/main.js b/funasr/runtime/html5/static/main.js
index 22f53c152..35e533a43 100644
--- a/funasr/runtime/html5/static/main.js
+++ b/funasr/runtime/html5/static/main.js
@@ -32,15 +32,121 @@ btnStart.disabled = true;
 btnConnect= document.getElementById('btnConnect');
 btnConnect.onclick = start;
  
-var rec_text="";
-var offline_text="";
+var rec_text="";  // for online rec asr result
+var offline_text=""; // for offline rec asr result
 var info_div = document.getElementById('info_div');
 
-//var now_ipaddress=window.location.href;
-//now_ipaddress=now_ipaddress.replace("https://","wss://");
-//now_ipaddress=now_ipaddress.replace("static/index.html","");
-//document.getElementById('wssip').value=now_ipaddress;
+var upfile = document.getElementById('upfile');
+
  
+
+var isfilemode=false;  // if it is in file mode
+var file_data_array;  // array to save file data
+var isconnected=0;    // for file rec, 0 is not begin, 1 is connected, -1 is error
+var totalsend=0;
+ 
+upfile.onchange = function () {
+　　　　　　var len = this.files.length;  
+            for(let i = 0; i < len; i++) {
+                let fileAudio = new FileReader();
+                fileAudio.readAsArrayBuffer(this.files[i]);  
+                fileAudio.onload = function() {
+                 var audioblob= fileAudio.result;
+				 file_data_array=audioblob;
+				 console.log(audioblob);
+                 btnConnect.disabled = false;
+                 info_div.innerHTML='请点击连接进行识别';
+               
+                }
+　　　　　　　　　　fileAudio.onerror = function(e) {
+　　　　　　　　　　　　console.log('error' + e);
+　　　　　　　　　　}
+            }
+        }
+
+function play_file()
+{
+		  var audioblob=new Blob( [ new Uint8Array(file_data_array)] , {type :"audio/wav"});
+		  var audio_record = document.getElementById('audio_record');
+		  audio_record.src =  (window.URL||webkitURL).createObjectURL(audioblob); 
+          audio_record.controls=true;
+		  audio_record.play(); 
+}
+function start_file_send()
+{
+		sampleBuf=new Int16Array( file_data_array );
+ 
+		var chunk_size=960; // for asr chunk_size [5, 10, 5]
+ 
+
+ 
+		
+ 
+		while(sampleBuf.length>=chunk_size){
+			
+		    sendBuf=sampleBuf.slice(0,chunk_size);
+			totalsend=totalsend+sampleBuf.length;
+			sampleBuf=sampleBuf.slice(chunk_size,sampleBuf.length);
+			wsconnecter.wsSend(sendBuf,false);
+ 
+		 
+		}
+ 
+		stop();
+
+ 
+
+}
+function start_file_offline()
+{             
+           	  console.log("start_file_offline",isconnected);  
+              if(isconnected==-1)
+			  {
+				  return;
+			  }
+		      if(isconnected==0){
+			   
+		        setTimeout(start_file_offline, 1000);
+				return;
+		      }
+			start_file_send();
+ 
+	         
+
+		 
+}
+	
+function on_recoder_mode_change()
+{
+            var item = null;
+            var obj = document.getElementsByName("recoder_mode");
+            for (var i = 0; i < obj.length; i++) { //遍历Radio 
+                if (obj[i].checked) {
+                    item = obj[i].value;  
+					break;
+                }
+		    
+
+           }
+		    if(item=="mic")
+			{
+				document.getElementById("mic_mode_div").style.display = 'block';
+				document.getElementById("rec_mode_div").style.display = 'none';
+ 
+				btnConnect.disabled=false;
+				isfilemode=false;
+			}
+			else
+			{
+				document.getElementById("mic_mode_div").style.display = 'none';
+				document.getElementById("rec_mode_div").style.display = 'block';
+                btnConnect.disabled = true;
+			    isfilemode=true;
+				info_div.innerHTML='请点击选择文件';
+			    
+	 
+			}
+}
 function getAsrMode(){
 
             var item = null;
@@ -53,7 +159,12 @@ function getAsrMode(){
 		    
 
            }
+            if(isfilemode)
+			{
+				item= "offline";
+			}
 		   console.log("asr mode"+item);
+		   
 		   return item;
 }
 		   
@@ -78,6 +189,18 @@ function getJsonMessage( jsonMsg ) {
 	varArea.value=rec_text;
 	console.log( "offline_text: " + asrmodel+","+offline_text);
 	console.log( "rec_text: " + rec_text);
+	if (isfilemode==true){
+		console.log("call stop ws!");
+		play_file();
+		wsconnecter.wsStop();
+        
+		info_div.innerHTML="请点击连接";
+		isconnected=0;
+		btnStart.disabled = true;
+		btnStop.disabled = true;
+		btnConnect.disabled=false;
+	}
+	
 	 
  
 }
@@ -86,14 +209,11 @@ function getJsonMessage( jsonMsg ) {
 function getConnState( connState ) {
 	if ( connState === 0 ) {
  
-		//rec.open( function(){
-		//	rec.start();
-		//	console.log("开始录音");
  
-		//});
-		btnStart.disabled = false;
-		btnConnect.disabled = true;
 		info_div.innerHTML='连接成功!请点击开始';
+		if (isfilemode==true){
+			info_div.innerHTML='请耐心等待,大文件等待时间更长';
+		}
 	} else if ( connState === 1 ) {
 		//stop();
 	} else if ( connState === 2 ) {
@@ -102,36 +222,52 @@ function getConnState( connState ) {
 		 
 		alert("连接地址"+document.getElementById('wssip').value+"失败,请检查asr地址和端口，并确保h5服务和asr服务在同一个域内。或换个浏览器试试。");
 		btnStart.disabled = true;
-
+		isconnected=0;
+ 
 		info_div.innerHTML='请点击连接';
 	}
 }
 
 function record()
 {
+ 
 		 rec.open( function(){
 		 rec.start();
 		 console.log("开始");
 		 btnStart.disabled = true;
 		 });
+ 
 }
+
+ 
+
 // 识别启动、停止、清空操作
 function start() {
 	
 	// 清除显示
 	clear();
 	//控件状态更新
- 	    
+ 	console.log("isfilemode"+isfilemode+","+isconnected);
     info_div.innerHTML="正在连接asr服务器，请等待...";
 	//启动连接
 	var ret=wsconnecter.wsStart();
 	if(ret==1){
 		isRec = true;
-		btnStart.disabled = true;
+		btnStart.disabled = false;
 		btnStop.disabled = false;
 		btnConnect.disabled=true;
-
+		if (isfilemode)
+		{
+                 console.log("start file now");
+			     start_file_offline();
+ 
+				 btnStart.disabled = true;
+		         btnStop.disabled = true;
+		         btnConnect.disabled = true;
+		}
+        return 1;
 	}
+	return 0;
 }
 
  
@@ -152,21 +288,26 @@ function stop() {
 		}
 	   wsconnecter.wsSend( JSON.stringify(request) ,false);
  
+	  
+	
 	 
-	
-	
 
-	
+	 //isconnected=0;
 	// 控件状态更新
+	
 	isRec = false;
-    info_div.innerHTML="请等候...";
-	btnStop.disabled = true;
-	setTimeout(function(){
-		console.log("call stop ws!");
-		wsconnecter.wsStop();
+    info_div.innerHTML="发送完数据,请等候,正在识别...";
+
+   if(isfilemode==false){
+	    btnStop.disabled = true;
 		btnStart.disabled = true;
 		btnConnect.disabled=false;
+	  setTimeout(function(){
+		console.log("call stop ws!");
+		wsconnecter.wsStop();
+        isconnected=0;
 		info_div.innerHTML="请点击连接";}, 3000 );
+	   
 	rec.stop(function(blob,duration){
   
 		console.log(blob);
@@ -189,8 +330,9 @@ function stop() {
 	},function(errMsg){
 		console.log("errMsg: " + errMsg);
 	});
+   }
     // 停止连接
-	
+ 
     
 
 }
diff --git a/funasr/runtime/html5/static/wsconnecter.js b/funasr/runtime/html5/static/wsconnecter.js
index 676a94ae5..b9098bb5a 100644
--- a/funasr/runtime/html5/static/wsconnecter.js
+++ b/funasr/runtime/html5/static/wsconnecter.js
@@ -15,8 +15,7 @@ function WebSocketConnectMethod( config ) { //定义socket连接方法类
 			  
 	this.wsStart = function () {
 		var Uri = document.getElementById('wssip').value; //"wss://111.205.137.58:5821/wss/" //设置wss asr online接口地址 如 wss://X.X.X.X:port/wss/
- 
-		if(Uri.match(/wss:\S*/))
+		if(Uri.match(/wss:\S*|ws:\S*/))
 		{
 			console.log("Uri"+Uri);
 		}
@@ -25,6 +24,7 @@ function WebSocketConnectMethod( config ) { //定义socket连接方法类
 			alert("请检查wss地址正确性");
 			return 0;
 		}
+ 
 		if ( 'WebSocket' in window ) {
 			speechSokt = new WebSocket( Uri ); // 定义socket连接对象
 			speechSokt.onopen = function(e){onOpen(e);}; // 定义响应函数
@@ -80,6 +80,7 @@ function WebSocketConnectMethod( config ) { //定义socket连接方法类
 		speechSokt.send( JSON.stringify(request) );
 		console.log("连接成功");
 		stateHandle(0);
+		isconnected=1;
 	}
 	
 	function onClose( e ) {
@@ -92,9 +93,11 @@ function WebSocketConnectMethod( config ) { //定义socket连接方法类
 	}
 	
 	function onError( e ) {
+		isconnected=-1;
 		info_div.innerHTML="连接"+e;
 		console.log(e);
 		stateHandle(2);
+		
 	}
     
  

From 113f8ea30a4a989a31ef993598fca0ff9158668b Mon Sep 17 00:00:00 2001
From: yhliang <68215459+yhliang-aslp@users.noreply.github.com>
Date: Tue, 20 Jun 2023 13:04:19 +0800
Subject: [PATCH 3/4] Dev lyh (#657)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

* update dev_lyh (#655)

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* update repo

* Java ws client support (#651)

* add java websocket support

* make little changes

* update repo

* update repo

* paraformer long cpu

* typeguard==2.13.3

* Update readme.md

* Update readme.md

* export

---------

Co-authored-by: 嘉渊 <wangjiaming.wjm@alibaba-inc.com>
Co-authored-by: zhaomingwork <61895407+zhaomingwork@users.noreply.github.com>
Co-authored-by: 游雁 <zhifu.gzf@alibaba-inc.com>
Co-authored-by: Yabin Li <wucong.lyb@alibaba-inc.com>

* fix mfcca

* update dev_lyh (#656)

* export

* update funasr-wss-client funasr-wss-server

---------

Co-authored-by: 游雁 <zhifu.gzf@alibaba-inc.com>
Co-authored-by: 雾聪 <wucong.lyb@alibaba-inc.com>

* Update default.py

* Update default.py

---------

Co-authored-by: 嘉渊 <wangjiaming.wjm@alibaba-inc.com>
Co-authored-by: zhaomingwork <61895407+zhaomingwork@users.noreply.github.com>
Co-authored-by: 游雁 <zhifu.gzf@alibaba-inc.com>
Co-authored-by: Yabin Li <wucong.lyb@alibaba-inc.com>
---
 .../sa_asr/conf/train_sa_asr_conformer.yaml   |   1 +
 funasr/models/frontend/default.py             | 101 +++++++++++-------
 2 files changed, 64 insertions(+), 38 deletions(-)

diff --git a/egs/alimeeting/sa_asr/conf/train_sa_asr_conformer.yaml b/egs/alimeeting/sa_asr/conf/train_sa_asr_conformer.yaml
index 47bc6bdb6..18614ddf3 100644
--- a/egs/alimeeting/sa_asr/conf/train_sa_asr_conformer.yaml
+++ b/egs/alimeeting/sa_asr/conf/train_sa_asr_conformer.yaml
@@ -10,6 +10,7 @@ frontend_conf:
     lfr_m: 1
     lfr_n: 1
     use_channel: 0
+    mc: False
 
 # encoder related
 asr_encoder: conformer
diff --git a/funasr/models/frontend/default.py b/funasr/models/frontend/default.py
index 6718f3f6c..abbcd1b05 100644
--- a/funasr/models/frontend/default.py
+++ b/funasr/models/frontend/default.py
@@ -77,8 +77,8 @@ class DefaultFrontend(AbsFrontend):
             htk=htk,
         )
         self.n_mels = n_mels
-        self.frontend_type = "default"
         self.use_channel = use_channel
+        self.frontend_type = "default"
 
     def output_size(self) -> int:
         return self.n_mels
@@ -146,9 +146,11 @@ class MultiChannelFrontend(AbsFrontend):
     def __init__(
             self,
             fs: Union[int, str] = 16000,
-            n_fft: int = 400,
-            frame_length: int = 25,
-            frame_shift: int = 10,
+            n_fft: int = 512,
+            win_length: int = None,
+            hop_length: int = None,
+            frame_length: int = None,
+            frame_shift: int = None,
             window: Optional[str] = "hann",
             center: bool = True,
             normalized: bool = False,
@@ -162,7 +164,8 @@ class MultiChannelFrontend(AbsFrontend):
             use_channel: int = None,
             lfr_m: int = 1,
             lfr_n: int = 1,
-            cmvn_file: str = None
+            cmvn_file: str = None,
+            mc: bool = True
     ):
         assert check_argument_types()
         super().__init__()
@@ -171,8 +174,18 @@ class MultiChannelFrontend(AbsFrontend):
 
         # Deepcopy (In general, dict shouldn't be used as default arg)
         frontend_conf = copy.deepcopy(frontend_conf)
-        self.win_length = frame_length * 16
-        self.hop_length = frame_shift * 16
+        if win_length is None and hop_length is None:
+            self.win_length = frame_length * 16
+            self.hop_length = frame_shift * 16
+        elif frame_length is None and frame_shift is None:
+            self.win_length = self.win_length
+            self.hop_length = self.hop_length
+        else:
+            logging.error(
+                "Only one of (win_length, hop_length) and (frame_length, frame_shift)"
+                "can be set."
+            )
+            exit(1)
 
         if apply_stft:
             self.stft = Stft(
@@ -202,17 +215,19 @@ class MultiChannelFrontend(AbsFrontend):
             htk=htk,
         )
         self.n_mels = n_mels
-        self.frontend_type = "default"
         self.use_channel = use_channel
-        if self.use_channel is not None:
-            logging.info("use the channel %d" % (self.use_channel))
-        else:
-            logging.info("random select channel")
-        self.cmvn_file = cmvn_file
-        if self.cmvn_file is not None:
-            mean, std = self._load_cmvn(self.cmvn_file)
-            self.register_buffer("mean", torch.from_numpy(mean))
-            self.register_buffer("std", torch.from_numpy(std))
+        self.mc = mc
+        if not self.mc:
+            if self.use_channel is not None:
+                logging.info("use the channel %d" % (self.use_channel))
+            else:
+                logging.info("random select channel")
+            self.cmvn_file = cmvn_file
+            if self.cmvn_file is not None:
+                mean, std = self._load_cmvn(self.cmvn_file)
+                self.register_buffer("mean", torch.from_numpy(mean))
+                self.register_buffer("std", torch.from_numpy(std))
+        self.frontend_type = "multichannelfrontend"
 
     def output_size(self) -> int:
         return self.n_mels
@@ -233,8 +248,8 @@ class MultiChannelFrontend(AbsFrontend):
             # input_stft: (Batch, Length, [Channel], Freq)
             input_stft, _, mask = self.frontend(input_stft, feats_lens)
 
-        # 3. [Multi channel case]: Select a channel
-        if input_stft.dim() == 4:
+        # 3. [Multi channel case]: Select a channel(sa_asr)
+        if input_stft.dim() == 4 and not self.mc:
             # h: (B, T, C, F) -> h: (B, T, F)
             if self.training:
                 if self.use_channel is not None:
@@ -256,27 +271,37 @@ class MultiChannelFrontend(AbsFrontend):
         # input_power: (Batch, [Channel,] Length, Freq)
         #       -> input_feats: (Batch, Length, Dim)
         input_feats, _ = self.logmel(input_power, feats_lens)
-        
-        # 6. Apply CMVN
-        if self.cmvn_file is not None:
-            if feats_lens is None:
-                feats_lens = input_feats.new_full([input_feats.size(0)], input_feats.size(1))
-            self.mean = self.mean.to(input_feats.device, input_feats.dtype)
-            self.std = self.std.to(input_feats.device, input_feats.dtype)
-            mask = make_pad_mask(feats_lens, input_feats, 1)
-
-            if input_feats.requires_grad:
-                input_feats = input_feats + self.mean
+        if self.mc:
+            # MFCCA
+            if input_feats.dim() ==4:
+                bt = input_feats.size(0)
+                channel_size = input_feats.size(2)
+                input_feats = input_feats.transpose(1,2).reshape(bt*channel_size,-1,80).contiguous()
+                feats_lens = feats_lens.repeat(1,channel_size).squeeze()
             else:
-                input_feats += self.mean
-            if input_feats.requires_grad:
-                input_feats = input_feats.masked_fill(mask, 0.0)
-            else:
-                input_feats.masked_fill_(mask, 0.0)
+                channel_size = 1
+            return input_feats, feats_lens, channel_size
+        else:
+            # 6. Apply CMVN
+            if self.cmvn_file is not None:
+                if feats_lens is None:
+                    feats_lens = input_feats.new_full([input_feats.size(0)], input_feats.size(1))
+                self.mean = self.mean.to(input_feats.device, input_feats.dtype)
+                self.std = self.std.to(input_feats.device, input_feats.dtype)
+                mask = make_pad_mask(feats_lens, input_feats, 1)
 
-            input_feats *= self.std
+                if input_feats.requires_grad:
+                    input_feats = input_feats + self.mean
+                else:
+                    input_feats += self.mean
+                if input_feats.requires_grad:
+                    input_feats = input_feats.masked_fill(mask, 0.0)
+                else:
+                    input_feats.masked_fill_(mask, 0.0)
 
-        return input_feats, feats_lens
+                input_feats *= self.std
+
+            return input_feats, feats_lens
 
     def _compute_stft(
             self, input: torch.Tensor, input_lengths: torch.Tensor
@@ -313,4 +338,4 @@ class MultiChannelFrontend(AbsFrontend):
                     continue
         means = np.array(means_list).astype(np.float)
         vars = np.array(vars_list).astype(np.float)
-        return means, vars
\ No newline at end of file
+        return means, vars

From c2a2575f198b1bfd452ea5769bec81bcce3d3a42 Mon Sep 17 00:00:00 2001
From: manyeyes <32889020+manyeyes@users.noreply.github.com>
Date: Wed, 21 Jun 2023 09:31:59 +0800
Subject: [PATCH 4/4] add c# assembly for fsmn vad (#650)

Co-authored-by: zx <12345678>
---
 .../AliFsmnVadSharp.Examples.csproj           |  18 +
 .../AliFsmnVadSharp.Examples/Program.cs       |  61 ++
 funasr/runtime/csharp/AliFsmnVadSharp.sln     |  37 +
 .../csharp/AliFsmnVadSharp/AliFsmnVad.cs      | 387 ++++++++++
 .../AliFsmnVadSharp/AliFsmnVadSharp.csproj    |  37 +
 .../AliFsmnVadSharp/DLL/KaldiNativeFbank.cs   |  40 +
 .../AliFsmnVadSharp/DLL/KnfOnlineFbank.cs     |  26 +
 .../csharp/AliFsmnVadSharp/E2EVadModel.cs     | 717 ++++++++++++++++++
 .../Lib/kaldi-native-fbank-dll.dll            | Bin 0 -> 487936 bytes
 .../AliFsmnVadSharp/Model/CmvnEntity.cs       |  17 +
 .../Model/E2EVadFrameProbEntity.cs            |  23 +
 .../Model/E2EVadSpeechBufWithDoaEntity.cs     |  98 +++
 .../Model/EncoderConfEntity.cs                |  35 +
 .../Model/FrontendConfEntity.cs               |  29 +
 .../AliFsmnVadSharp/Model/SegmentEntity.cs    |  22 +
 .../AliFsmnVadSharp/Model/VadInputEntity.cs   |  23 +
 .../AliFsmnVadSharp/Model/VadOutputEntity.cs  |  19 +
 .../Model/VadPostConfEntity.cs                |  72 ++
 .../AliFsmnVadSharp/Model/VadYamlEntity.cs    |  27 +
 .../AliFsmnVadSharp/Struct/FbankData.cs       |   6 +
 .../AliFsmnVadSharp/Utils/YamlHelper.cs       |  28 +
 .../csharp/AliFsmnVadSharp/WavFrontend.cs     | 185 +++++
 .../csharp/AliFsmnVadSharp/WindowDetector.cs  | 156 ++++
 funasr/runtime/csharp/README.md               |  59 ++
 24 files changed, 2122 insertions(+)
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp.Examples/AliFsmnVadSharp.Examples.csproj
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp.Examples/Program.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp.sln
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/AliFsmnVad.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/AliFsmnVadSharp.csproj
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/DLL/KaldiNativeFbank.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/DLL/KnfOnlineFbank.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/E2EVadModel.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/Lib/kaldi-native-fbank-dll.dll
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/Model/CmvnEntity.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/Model/E2EVadFrameProbEntity.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/Model/E2EVadSpeechBufWithDoaEntity.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/Model/EncoderConfEntity.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/Model/FrontendConfEntity.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/Model/SegmentEntity.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/Model/VadInputEntity.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/Model/VadOutputEntity.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/Model/VadPostConfEntity.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/Model/VadYamlEntity.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/Struct/FbankData.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/Utils/YamlHelper.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/WavFrontend.cs
 create mode 100644 funasr/runtime/csharp/AliFsmnVadSharp/WindowDetector.cs
 create mode 100644 funasr/runtime/csharp/README.md

diff --git a/funasr/runtime/csharp/AliFsmnVadSharp.Examples/AliFsmnVadSharp.Examples.csproj b/funasr/runtime/csharp/AliFsmnVadSharp.Examples/AliFsmnVadSharp.Examples.csproj
new file mode 100644
index 000000000..b494bb50c
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp.Examples/AliFsmnVadSharp.Examples.csproj
@@ -0,0 +1,18 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net6.0</TargetFramework>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="NAudio" Version="2.1.0" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\AliFsmnVadSharp\AliFsmnVadSharp.csproj" />
+  </ItemGroup>
+
+</Project>
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp.Examples/Program.cs b/funasr/runtime/csharp/AliFsmnVadSharp.Examples/Program.cs
new file mode 100644
index 000000000..dd3bf78b9
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp.Examples/Program.cs
@@ -0,0 +1,61 @@
+using AliFsmnVadSharp;
+using AliFsmnVadSharp.Model;
+using NAudio.Wave;
+
+internal static class Program
+{
+	[STAThread]
+	private static void Main()
+	{
+		string applicationBase = AppDomain.CurrentDomain.BaseDirectory;
+		string modelFilePath = applicationBase + "./speech_fsmn_vad_zh-cn-16k-common-pytorch/model.onnx";
+		string configFilePath = applicationBase + "./speech_fsmn_vad_zh-cn-16k-common-pytorch/vad.yaml";
+		string mvnFilePath = applicationBase + "./speech_fsmn_vad_zh-cn-16k-common-pytorch/vad.mvn";
+		int batchSize = 2;
+		TimeSpan start_time0 = new TimeSpan(DateTime.Now.Ticks);
+		AliFsmnVad aliFsmnVad = new AliFsmnVad(modelFilePath, configFilePath, mvnFilePath, batchSize);
+		TimeSpan end_time0 = new TimeSpan(DateTime.Now.Ticks);
+		double elapsed_milliseconds0 = end_time0.TotalMilliseconds - start_time0.TotalMilliseconds;
+		Console.WriteLine("load model and init config elapsed_milliseconds:{0}", elapsed_milliseconds0.ToString());
+		List<float[]> samples = new List<float[]>();
+		TimeSpan total_duration = new TimeSpan(0L);
+		for (int i = 0; i < 2; i++)
+		{
+			string wavFilePath = string.Format(applicationBase + "./speech_fsmn_vad_zh-cn-16k-common-pytorch/example/{0}.wav", i.ToString());//vad_example
+			if (!File.Exists(wavFilePath))
+			{
+				continue;
+			}
+			AudioFileReader _audioFileReader = new AudioFileReader(wavFilePath);
+			byte[] datas = new byte[_audioFileReader.Length];
+			_audioFileReader.Read(datas, 0, datas.Length);
+			TimeSpan duration = _audioFileReader.TotalTime;
+			float[] wavdata = new float[datas.Length / 4];
+			Buffer.BlockCopy(datas, 0, wavdata, 0, datas.Length);
+			float[] sample = wavdata.Select((float x) => x * 32768f).ToArray();
+			samples.Add(wavdata);
+			total_duration += duration;			
+		}
+		TimeSpan start_time = new TimeSpan(DateTime.Now.Ticks);
+		//SegmentEntity[] segments_duration = aliFsmnVad.GetSegments(samples);
+		SegmentEntity[] segments_duration = aliFsmnVad.GetSegmentsByStep(samples);
+		TimeSpan end_time = new TimeSpan(DateTime.Now.Ticks);
+		Console.WriteLine("vad infer result:");
+		foreach (SegmentEntity segment in segments_duration)
+		{
+			Console.Write("[");
+			foreach (var x in segment.Segment) 
+			{
+				Console.Write("[" + string.Join(",", x.ToArray()) + "]");
+			}
+			Console.Write("]\r\n");
+		}
+
+		double elapsed_milliseconds = end_time.TotalMilliseconds - start_time.TotalMilliseconds;
+		double rtf = elapsed_milliseconds / total_duration.TotalMilliseconds;
+		Console.WriteLine("elapsed_milliseconds:{0}", elapsed_milliseconds.ToString());
+		Console.WriteLine("total_duration:{0}", total_duration.TotalMilliseconds.ToString());
+		Console.WriteLine("rtf:{1}", "0".ToString(), rtf.ToString());
+		Console.WriteLine("------------------------");
+	}
+}
\ No newline at end of file
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp.sln b/funasr/runtime/csharp/AliFsmnVadSharp.sln
new file mode 100644
index 000000000..8bf24aa81
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp.sln
@@ -0,0 +1,37 @@
+
+Microsoft Visual Studio Solution File, Format Version 12.00
+# Visual Studio Version 17
+VisualStudioVersion = 17.1.32210.238
+MinimumVisualStudioVersion = 10.0.40219.1
+Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "AliFsmnVadSharp", "AliFsmnVadSharp\AliFsmnVadSharp.csproj", "{BFB82F2E-AD5B-405C-AAFF-3CE33C548748}"
+EndProject
+Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "AliFsmnVadSharp.Examples", "AliFsmnVadSharp.Examples\AliFsmnVadSharp.Examples.csproj", "{2FFA4D03-A62B-435B-B57B-7E49209810E1}"
+EndProject
+Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Solution Items", "Solution Items", "{212561CC-9836-4F45-A31B-298EF576F519}"
+	ProjectSection(SolutionItems) = preProject
+		license = license
+		README.md = README.md
+	EndProjectSection
+EndProject
+Global
+	GlobalSection(SolutionConfigurationPlatforms) = preSolution
+		Debug|Any CPU = Debug|Any CPU
+		Release|Any CPU = Release|Any CPU
+	EndGlobalSection
+	GlobalSection(ProjectConfigurationPlatforms) = postSolution
+		{BFB82F2E-AD5B-405C-AAFF-3CE33C548748}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{BFB82F2E-AD5B-405C-AAFF-3CE33C548748}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{BFB82F2E-AD5B-405C-AAFF-3CE33C548748}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{BFB82F2E-AD5B-405C-AAFF-3CE33C548748}.Release|Any CPU.Build.0 = Release|Any CPU
+		{2FFA4D03-A62B-435B-B57B-7E49209810E1}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{2FFA4D03-A62B-435B-B57B-7E49209810E1}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{2FFA4D03-A62B-435B-B57B-7E49209810E1}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{2FFA4D03-A62B-435B-B57B-7E49209810E1}.Release|Any CPU.Build.0 = Release|Any CPU
+	EndGlobalSection
+	GlobalSection(SolutionProperties) = preSolution
+		HideSolutionNode = FALSE
+	EndGlobalSection
+	GlobalSection(ExtensibilityGlobals) = postSolution
+		SolutionGuid = {FCC1BBCC-91A3-4223-B368-D272FB5108B6}
+	EndGlobalSection
+EndGlobal
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/AliFsmnVad.cs b/funasr/runtime/csharp/AliFsmnVadSharp/AliFsmnVad.cs
new file mode 100644
index 000000000..f42bfb12e
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/AliFsmnVad.cs
@@ -0,0 +1,387 @@
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+using Microsoft.ML;
+using Microsoft.ML.OnnxRuntime;
+using Microsoft.ML.OnnxRuntime.Tensors;
+using Microsoft.Extensions.Logging;
+using AliFsmnVadSharp.Model;
+using AliFsmnVadSharp.Utils;
+
+namespace AliFsmnVadSharp
+{
+    public class AliFsmnVad
+    {
+        private InferenceSession _onnxSession;
+        private readonly ILogger<AliFsmnVad> _logger;
+        private string _frontend;
+        private WavFrontend _wavFrontend;
+        private int _batchSize = 1;
+        private int _max_end_sil = int.MinValue;
+        private EncoderConfEntity _encoderConfEntity;
+        private VadPostConfEntity _vad_post_conf;
+
+        public AliFsmnVad(string modelFilePath, string configFilePath, string mvnFilePath, int batchSize = 1)
+        {
+            Microsoft.ML.OnnxRuntime.SessionOptions options = new Microsoft.ML.OnnxRuntime.SessionOptions();
+            options.AppendExecutionProvider_CPU(0);
+            options.InterOpNumThreads = 1;
+            _onnxSession = new InferenceSession(modelFilePath, options);
+
+            VadYamlEntity vadYamlEntity = YamlHelper.ReadYaml<VadYamlEntity>(configFilePath);
+            _wavFrontend = new WavFrontend(mvnFilePath, vadYamlEntity.frontend_conf);
+            _frontend = vadYamlEntity.frontend;
+            _vad_post_conf = vadYamlEntity.vad_post_conf;
+            _batchSize = batchSize;
+            _max_end_sil = _max_end_sil != int.MinValue ? _max_end_sil : vadYamlEntity.vad_post_conf.max_end_silence_time;
+            _encoderConfEntity = vadYamlEntity.encoder_conf;
+
+            ILoggerFactory loggerFactory = new LoggerFactory();
+            _logger = new Logger<AliFsmnVad>(loggerFactory);
+        }
+
+        public SegmentEntity[] GetSegments(List<float[]> samples)
+        {
+            int waveform_nums = samples.Count;
+            _batchSize = Math.Min(waveform_nums, _batchSize);
+            SegmentEntity[] segments = new SegmentEntity[waveform_nums];
+            for (int beg_idx = 0; beg_idx < waveform_nums; beg_idx += _batchSize)
+            {
+                int end_idx = Math.Min(waveform_nums, beg_idx + _batchSize);
+                List<float[]> waveform_list = new List<float[]>();
+                for (int i = beg_idx; i < end_idx; i++)
+                {
+                    waveform_list.Add(samples[i]);
+                }
+                List<VadInputEntity> vadInputEntitys = ExtractFeats(waveform_list);
+                try
+                {
+                    int t_offset = 0;
+                    int step = Math.Min(waveform_list.Max(x => x.Length), 6000);
+                    bool is_final = true;
+                    List<VadOutputEntity> vadOutputEntitys = Infer(vadInputEntitys);
+                    for (int batch_num = beg_idx; batch_num < end_idx; batch_num++)
+                    {
+                        var scores = vadOutputEntitys[batch_num - beg_idx].Scores;
+                        SegmentEntity[] segments_part = vadInputEntitys[batch_num].VadScorer.DefaultCall(scores, waveform_list[batch_num - beg_idx], is_final: is_final, max_end_sil: _max_end_sil, online: false);
+                        if (segments_part.Length > 0)
+                        {
+#pragma warning disable CS8602 // 解引用可能出现空引用。
+                            if (segments[batch_num] == null)
+                            {
+                                segments[batch_num] = new SegmentEntity();
+                            }
+                            segments[batch_num].Segment.AddRange(segments_part[0].Segment); //
+#pragma warning restore CS8602 // 解引用可能出现空引用。
+
+                        }
+                    }
+                }
+                catch (OnnxRuntimeException ex)
+                {
+                    _logger.LogWarning("input wav is silence or noise");
+                    segments = null;
+                }
+//                for (int batch_num = 0; batch_num < _batchSize; batch_num++)
+//                {
+//                    List<float[]> segment_waveforms = new List<float[]>();
+//                    foreach (int[] segment in segments[beg_idx + batch_num].Segment)
+//                    {
+//                        // (int)(16000 * (segment[0] / 1000.0) * 2);
+//                        int frame_length = (((6000 * 400) / 400 - 1) * 160 + 400) / 60 / 1000;
+//                        int frame_start = segment[0] * frame_length;
+//                        int frame_end = segment[1] * frame_length;
+//                        float[] segment_waveform = new float[frame_end - frame_start];
+//                        Array.Copy(waveform_list[batch_num], frame_start, segment_waveform, 0, segment_waveform.Length);
+//                        segment_waveforms.Add(segment_waveform);
+//                    }
+//                    segments[beg_idx + batch_num].Waveform.AddRange(segment_waveforms);
+//                }
+            }
+
+            return segments;
+        }
+
+        public SegmentEntity[] GetSegmentsByStep(List<float[]> samples)
+        {
+            int waveform_nums = samples.Count;
+            _batchSize=Math.Min(waveform_nums, _batchSize);
+            SegmentEntity[] segments = new SegmentEntity[waveform_nums];
+            for (int beg_idx = 0; beg_idx < waveform_nums; beg_idx += _batchSize)
+            {
+                int end_idx = Math.Min(waveform_nums, beg_idx + _batchSize);
+                List<float[]> waveform_list = new List<float[]>();
+                for (int i = beg_idx; i < end_idx; i++)
+                {
+                    waveform_list.Add(samples[i]);
+                }
+                List<VadInputEntity> vadInputEntitys = ExtractFeats(waveform_list);
+                int feats_len = vadInputEntitys.Max(x => x.SpeechLength);
+                List<float[]> in_cache = new List<float[]>();
+                in_cache = PrepareCache(in_cache);
+                try
+                {
+                    int step = Math.Min(vadInputEntitys.Max(x => x.SpeechLength), 6000 * 400);
+                    bool is_final = true;
+                    for (int t_offset = 0; t_offset < (int)(feats_len); t_offset += Math.Min(step, feats_len - t_offset))
+                    {
+
+                        if (t_offset + step >= feats_len - 1)
+                        {
+                            step = feats_len - t_offset;
+                            is_final = true;
+                        }
+                        else
+                        {
+                            is_final = false;
+                        }
+                        List<VadInputEntity> vadInputEntitys_step = new List<VadInputEntity>();
+                        foreach (VadInputEntity vadInputEntity in vadInputEntitys)
+                        {
+                            VadInputEntity vadInputEntity_step = new VadInputEntity();
+                            float[]? feats = vadInputEntity.Speech;
+                            int curr_step = Math.Min(feats.Length - t_offset, step);
+                            if (curr_step <= 0)
+                            {
+                                vadInputEntity_step.Speech = new float[32000];
+                                vadInputEntity_step.SpeechLength = 0;
+                                vadInputEntity_step.InCaches = in_cache;
+                                vadInputEntity_step.Waveform = new float[(((int)(32000) / 400 - 1) * 160 + 400)];
+                                vadInputEntitys_step.Add(vadInputEntity_step);
+                                continue;
+                            }
+                            float[]? feats_step = new float[curr_step];
+                            Array.Copy(feats, t_offset, feats_step, 0, feats_step.Length);
+                            float[]? waveform = vadInputEntity.Waveform;
+                            float[]? waveform_step = new float[Math.Min(waveform.Length, ((int)(t_offset + step) / 400 - 1) * 160 + 400) - t_offset / 400 * 160];
+                            Array.Copy(waveform, t_offset / 400 * 160, waveform_step, 0, waveform_step.Length);
+                            vadInputEntity_step.Speech = feats_step;
+                            vadInputEntity_step.SpeechLength = feats_step.Length;
+                            vadInputEntity_step.InCaches = vadInputEntity.InCaches;
+                            vadInputEntity_step.Waveform = waveform_step;
+                            vadInputEntitys_step.Add(vadInputEntity_step);
+                        }
+                        List<VadOutputEntity> vadOutputEntitys = Infer(vadInputEntitys_step);
+                        for (int batch_num = 0; batch_num < _batchSize; batch_num++)
+                        {
+                            vadInputEntitys[batch_num].InCaches = vadOutputEntitys[batch_num].OutCaches;
+                            var scores = vadOutputEntitys[batch_num].Scores;
+                            SegmentEntity[] segments_part = vadInputEntitys[batch_num].VadScorer.DefaultCall(scores, vadInputEntitys_step[batch_num].Waveform, is_final: is_final, max_end_sil: _max_end_sil, online: false);
+                            if (segments_part.Length > 0)
+                            {
+
+#pragma warning disable CS8602 // 解引用可能出现空引用。
+                                if (segments[beg_idx + batch_num] == null)
+                                {
+                                    segments[beg_idx + batch_num] = new SegmentEntity();
+                                }
+                                if (segments_part[0] != null)
+                                {
+                                    segments[beg_idx + batch_num].Segment.AddRange(segments_part[0].Segment);
+                                }
+#pragma warning restore CS8602 // 解引用可能出现空引用。
+
+                            }
+                        }
+                    }
+                }
+                catch (OnnxRuntimeException ex)
+                {
+                    _logger.LogWarning("input wav is silence or noise");
+                    segments = null;
+                }
+//                for (int batch_num = 0; batch_num < _batchSize; batch_num++)
+//                {
+//                    List<float[]> segment_waveforms=new List<float[]>();
+//                    foreach (int[] segment in segments[beg_idx + batch_num].Segment)
+//                    {
+//                        // (int)(16000 * (segment[0] / 1000.0) * 2);
+//                        int frame_length = (((6000 * 400) / 400 - 1) * 160 + 400) / 60 / 1000;
+//                        int frame_start = segment[0] * frame_length;
+//                        int frame_end = segment[1] * frame_length;
+//                        if(frame_end > waveform_list[batch_num].Length)
+//                        {
+//                            break;
+//                        }
+//                        float[] segment_waveform = new float[frame_end - frame_start];
+//                        Array.Copy(waveform_list[batch_num], frame_start, segment_waveform, 0, segment_waveform.Length);
+//                        segment_waveforms.Add(segment_waveform);
+//                    }
+//                    segments[beg_idx + batch_num].Waveform.AddRange(segment_waveforms);
+//                }
+
+            }
+            return segments;
+        }
+
+        private List<float[]> PrepareCache(List<float[]> in_cache)
+        {
+            if (in_cache.Count > 0)
+            {
+                return in_cache;
+            }
+
+            int fsmn_layers = _encoderConfEntity.fsmn_layers;
+
+            int proj_dim = _encoderConfEntity.proj_dim;
+            int lorder = _encoderConfEntity.lorder;
+
+            for (int i = 0; i < fsmn_layers; i++)
+            {
+                float[] cache = new float[1 * proj_dim * (lorder - 1) * 1];
+                in_cache.Add(cache);
+            }
+            return in_cache;
+        }
+
+        private List<VadInputEntity> ExtractFeats(List<float[]> waveform_list)
+        {
+            List<float[]> in_cache = new List<float[]>();
+            in_cache = PrepareCache(in_cache);
+            List<VadInputEntity> vadInputEntitys = new List<VadInputEntity>();
+            foreach (var waveform in waveform_list)
+            {
+                float[] fbanks = _wavFrontend.GetFbank(waveform);
+                float[] features = _wavFrontend.LfrCmvn(fbanks);
+                VadInputEntity vadInputEntity = new VadInputEntity();
+                vadInputEntity.Waveform = waveform;
+                vadInputEntity.Speech = features;
+                vadInputEntity.SpeechLength = features.Length;
+                vadInputEntity.InCaches = in_cache;
+                vadInputEntity.VadScorer = new E2EVadModel(_vad_post_conf);
+                vadInputEntitys.Add(vadInputEntity);
+            }
+            return vadInputEntitys;
+        }
+        /// <summary>
+        /// 一维数组转3维数组
+        /// </summary>
+        /// <param name="obj"></param>
+        /// <param name="len">一维长</param>
+        /// <param name="wid">二维长</param>
+        /// <returns></returns>
+        public static T[,,] DimOneToThree<T>(T[] oneDimObj, int len, int wid)
+        {
+            if (oneDimObj.Length % (len * wid) != 0)
+                return null;
+            int height = oneDimObj.Length / (len * wid);
+            T[,,] threeDimObj = new T[len, wid, height];
+
+            for (int i = 0; i < oneDimObj.Length; i++)
+            {
+                threeDimObj[i / (wid * height), (i / height) % wid, i % height] = oneDimObj[i];
+            }
+            return threeDimObj;
+        }
+
+        private List<VadOutputEntity> Infer(List<VadInputEntity> vadInputEntitys)
+        {
+            List<VadOutputEntity> vadOutputEntities = new List<VadOutputEntity>();
+            foreach (VadInputEntity vadInputEntity in vadInputEntitys)
+            {
+                int batchSize = 1;//_batchSize                
+                var inputMeta = _onnxSession.InputMetadata;
+                var container = new List<NamedOnnxValue>();
+                int[] dim = new int[] { batchSize, vadInputEntity.Speech.Length / 400 / batchSize, 400 };
+                var tensor = new DenseTensor<float>(vadInputEntity.Speech, dim, false);
+                container.Add(NamedOnnxValue.CreateFromTensor<float>("speech", tensor));
+
+                int i = 0;
+                foreach (var cache in vadInputEntity.InCaches)
+                {
+                    int[] cache_dim = new int[] { 1, 128, cache.Length / 128 / 1, 1 };
+                    var cache_tensor = new DenseTensor<float>(cache, cache_dim, false);
+                    container.Add(NamedOnnxValue.CreateFromTensor<float>("in_cache" + i.ToString(), cache_tensor));
+                    i++;
+                }
+
+                IDisposableReadOnlyCollection<DisposableNamedOnnxValue> results = _onnxSession.Run(container);
+                var resultsArray = results.ToArray();
+                VadOutputEntity vadOutputEntity = new VadOutputEntity();
+                for (int j = 0; j < resultsArray.Length; j++)
+                {
+                    if (resultsArray[j].Name.Equals("logits"))
+                    {
+                        Tensor<float> tensors = resultsArray[0].AsTensor<float>();
+                        var _scores = DimOneToThree<float>(tensors.ToArray(), 1, tensors.Dimensions[1]);
+                        vadOutputEntity.Scores = _scores;
+                    }
+                    if (resultsArray[j].Name.StartsWith("out_cache"))
+                    {
+                        vadOutputEntity.OutCaches.Add(resultsArray[j].AsEnumerable<float>().ToArray());
+                    }
+
+                }
+                vadOutputEntities.Add(vadOutputEntity);
+            }
+
+            return vadOutputEntities;
+        }
+
+        private float[] PadSequence(List<VadInputEntity> modelInputs)
+        {
+            int max_speech_length = modelInputs.Max(x => x.SpeechLength);
+            int speech_length = max_speech_length * modelInputs.Count;
+            float[] speech = new float[speech_length];
+            float[,] xxx = new float[modelInputs.Count, max_speech_length];
+            for (int i = 0; i < modelInputs.Count; i++)
+            {
+                if (max_speech_length == modelInputs[i].SpeechLength)
+                {
+                    for (int j = 0; j < xxx.GetLength(1); j++)
+                    {
+#pragma warning disable CS8602 // 解引用可能出现空引用。
+                        xxx[i, j] = modelInputs[i].Speech[j];
+#pragma warning restore CS8602 // 解引用可能出现空引用。
+                    }
+                    continue;
+                }
+                float[] nullspeech = new float[max_speech_length - modelInputs[i].SpeechLength];
+                float[]? curr_speech = modelInputs[i].Speech;
+                float[] padspeech = new float[max_speech_length];
+                // ///////////////////////////////////////////////////
+                var arr_neg_mean = _onnxSession.ModelMetadata.CustomMetadataMap["neg_mean"].ToString().Split(',').ToArray();
+                double[] neg_mean = arr_neg_mean.Select(x => (double)Convert.ToDouble(x)).ToArray();
+                var arr_inv_stddev = _onnxSession.ModelMetadata.CustomMetadataMap["inv_stddev"].ToString().Split(',').ToArray();
+                double[] inv_stddev = arr_inv_stddev.Select(x => (double)Convert.ToDouble(x)).ToArray();
+
+                int dim = neg_mean.Length;
+                for (int j = 0; j < max_speech_length; j++)
+                {
+                    int k = new Random().Next(0, dim);
+                    padspeech[j] = (float)((float)(0 + neg_mean[k]) * inv_stddev[k]);
+                }
+                Array.Copy(curr_speech, 0, padspeech, 0, curr_speech.Length);
+                for (int j = 0; j < padspeech.Length; j++)
+                {
+#pragma warning disable CS8602 // 解引用可能出现空引用。
+                    xxx[i, j] = padspeech[j];
+#pragma warning restore CS8602 // 解引用可能出现空引用。
+                }
+
+            }
+            int s = 0;
+            for (int i = 0; i < xxx.GetLength(0); i++)
+            {
+                for (int j = 0; j < xxx.GetLength(1); j++)
+                {
+                    speech[s] = xxx[i, j];
+                    s++;
+                }
+            }
+            return speech;
+        }
+
+
+
+
+
+
+
+
+
+
+
+
+    }
+}
\ No newline at end of file
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/AliFsmnVadSharp.csproj b/funasr/runtime/csharp/AliFsmnVadSharp/AliFsmnVadSharp.csproj
new file mode 100644
index 000000000..49915173e
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/AliFsmnVadSharp.csproj
@@ -0,0 +1,37 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <TargetFramework>net6.0</TargetFramework>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Extensions.Logging" Version="7.0.0" />
+    <PackageReference Include="Microsoft.ML.OnnxRuntime" Version="1.15.0" />
+    <PackageReference Include="YamlDotNet" Version="13.1.0" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <None Update="Lib\kaldi-native-fbank-dll.dll">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+			<TargetPath>kaldi-native-fbank-dll.dll</TargetPath>
+    </None>
+    <None Update="speech_fsmn_vad_zh-cn-16k-common-pytorch\example\0.wav">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+    <None Update="speech_fsmn_vad_zh-cn-16k-common-pytorch\example\1.wav">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+    <None Update="speech_fsmn_vad_zh-cn-16k-common-pytorch\model.onnx">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+    <None Update="speech_fsmn_vad_zh-cn-16k-common-pytorch\vad.mvn">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+    <None Update="speech_fsmn_vad_zh-cn-16k-common-pytorch\vad.yaml">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+  </ItemGroup>
+
+</Project>
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/DLL/KaldiNativeFbank.cs b/funasr/runtime/csharp/AliFsmnVadSharp/DLL/KaldiNativeFbank.cs
new file mode 100644
index 000000000..af0ad3664
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/DLL/KaldiNativeFbank.cs
@@ -0,0 +1,40 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+using System.Runtime.InteropServices;
+using AliFsmnVadSharp.Struct;
+
+namespace AliFsmnVadSharp.DLL
+{
+    public static class KaldiNativeFbank
+    {
+        private const string dllName = @"kaldi-native-fbank-dll";
+
+        [DllImport(dllName, EntryPoint = "GetFbankOptions", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]
+        internal static extern IntPtr GetFbankOptions(float dither, bool snip_edges, float sample_rate, int num_bins, float frame_shift = 10.0f, float frame_length = 25.0f, float energy_floor = 0.0f, bool debug_mel = false, string window_type = "hamming");
+
+        [DllImport(dllName, EntryPoint = "GetOnlineFbank", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]
+        internal static extern KnfOnlineFbank GetOnlineFbank(IntPtr opts);
+
+        [DllImport(dllName, EntryPoint = "AcceptWaveform", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]
+        internal static extern void AcceptWaveform(KnfOnlineFbank knfOnlineFbank, float sample_rate, float[] samples, int samples_size);
+
+        [DllImport(dllName, EntryPoint = "InputFinished", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]
+        internal static extern void InputFinished(KnfOnlineFbank knfOnlineFbank);
+
+        [DllImport(dllName, EntryPoint = "GetNumFramesReady", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]
+        internal static extern int GetNumFramesReady(KnfOnlineFbank knfOnlineFbank);
+
+        [DllImport(dllName, EntryPoint = "AcceptWaveformxxx", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]
+        internal static extern FbankDatas AcceptWaveformxxx(KnfOnlineFbank knfOnlineFbank, float sample_rate, float[] samples, int samples_size);
+
+        [DllImport(dllName, EntryPoint = "GetFbank", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]
+        internal static extern void GetFbank(KnfOnlineFbank knfOnlineFbank,int frame, ref FbankData pData);
+
+        [DllImport(dllName, EntryPoint = "GetFbanks", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]
+        internal static extern void GetFbanks(KnfOnlineFbank knfOnlineFbank, int framesNum, ref FbankDatas fbankDatas);
+        
+    }
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/DLL/KnfOnlineFbank.cs b/funasr/runtime/csharp/AliFsmnVadSharp/DLL/KnfOnlineFbank.cs
new file mode 100644
index 000000000..45549b2bf
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/DLL/KnfOnlineFbank.cs
@@ -0,0 +1,26 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Runtime.InteropServices;
+using System.Text;
+using System.Threading.Tasks;
+
+namespace AliFsmnVadSharp.DLL
+{
+    internal struct FbankData
+    {
+        public IntPtr data;
+        public int data_length;
+    };
+
+    internal struct FbankDatas
+    {
+        public IntPtr data;
+        public int data_length;
+    };
+
+    internal struct KnfOnlineFbank
+    {
+        public IntPtr impl;
+    };
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/E2EVadModel.cs b/funasr/runtime/csharp/AliFsmnVadSharp/E2EVadModel.cs
new file mode 100644
index 000000000..ce519b1e9
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/E2EVadModel.cs
@@ -0,0 +1,717 @@
+using System;
+using System.Collections.Generic;
+using System.Diagnostics;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+using AliFsmnVadSharp.Model;
+
+namespace AliFsmnVadSharp
+{
+    enum VadStateMachine
+    {
+        kVadInStateStartPointNotDetected = 1,
+        kVadInStateInSpeechSegment = 2,
+        kVadInStateEndPointDetected = 3,
+    }
+    enum VadDetectMode
+    {
+        kVadSingleUtteranceDetectMode = 0,
+        kVadMutipleUtteranceDetectMode = 1,
+    }
+
+
+    internal class E2EVadModel
+    {
+        private VadPostConfEntity _vad_opts = new VadPostConfEntity();
+        private WindowDetector _windows_detector = new WindowDetector();
+        private bool _is_final = false;
+        private int _data_buf_start_frame = 0;
+        private int _frm_cnt = 0;
+        private int _latest_confirmed_speech_frame = 0;
+        private int _lastest_confirmed_silence_frame = -1;
+        private int _continous_silence_frame_count = 0;
+        private int _vad_state_machine = (int)VadStateMachine.kVadInStateStartPointNotDetected;
+        private int _confirmed_start_frame = -1;
+        private int _confirmed_end_frame = -1;
+        private int _number_end_time_detected = 0;
+        private int _sil_frame = 0;
+        private int[] _sil_pdf_ids = new int[0];
+        private double _noise_average_decibel = -100.0D;
+        private bool _pre_end_silence_detected = false;
+        private bool _next_seg = true;
+
+        private List<E2EVadSpeechBufWithDoaEntity> _output_data_buf;
+        private int _output_data_buf_offset = 0;
+        private List<E2EVadFrameProbEntity> _frame_probs = new List<E2EVadFrameProbEntity>();
+        private int _max_end_sil_frame_cnt_thresh = 800 - 150;
+        private float _speech_noise_thres = 0.6F;
+        private float[,,] _scores = null;
+        private int _idx_pre_chunk = 0;
+        private bool _max_time_out = false;
+        private List<double> _decibel = new List<double>();
+        private int _data_buf_size = 0;
+        private int _data_buf_all_size = 0;
+
+        public E2EVadModel(VadPostConfEntity vadPostConfEntity)
+        {
+            _vad_opts = vadPostConfEntity;
+            _windows_detector = new WindowDetector(_vad_opts.window_size_ms,
+                                                   _vad_opts.sil_to_speech_time_thres,
+                                                   _vad_opts.speech_to_sil_time_thres,
+                                                   _vad_opts.frame_in_ms);
+            AllResetDetection();
+        }
+
+        private void AllResetDetection()
+        {
+            _is_final = false;
+            _data_buf_start_frame = 0;
+            _frm_cnt = 0;
+            _latest_confirmed_speech_frame = 0;
+            _lastest_confirmed_silence_frame = -1;
+            _continous_silence_frame_count = 0;
+            _vad_state_machine = (int)VadStateMachine.kVadInStateStartPointNotDetected;
+            _confirmed_start_frame = -1;
+            _confirmed_end_frame = -1;
+            _number_end_time_detected = 0;
+            _sil_frame = 0;
+            _sil_pdf_ids = _vad_opts.sil_pdf_ids;
+            _noise_average_decibel = -100.0F;
+            _pre_end_silence_detected = false;
+            _next_seg = true;
+
+            _output_data_buf = new List<E2EVadSpeechBufWithDoaEntity>();
+            _output_data_buf_offset = 0;
+            _frame_probs = new List<E2EVadFrameProbEntity>();
+            _max_end_sil_frame_cnt_thresh = _vad_opts.max_end_silence_time - _vad_opts.speech_to_sil_time_thres;
+            _speech_noise_thres = _vad_opts.speech_noise_thres;
+            _scores = null;
+            _idx_pre_chunk = 0;
+            _max_time_out = false;
+            _decibel = new List<double>();
+            _data_buf_size = 0;
+            _data_buf_all_size = 0;
+            ResetDetection();
+        }
+
+        private void ResetDetection()
+        {
+            _continous_silence_frame_count = 0;
+            _latest_confirmed_speech_frame = 0;
+            _lastest_confirmed_silence_frame = -1;
+            _confirmed_start_frame = -1;
+            _confirmed_end_frame = -1;
+            _vad_state_machine = (int)VadStateMachine.kVadInStateStartPointNotDetected;
+            _windows_detector.Reset();
+            _sil_frame = 0;
+            _frame_probs = new List<E2EVadFrameProbEntity>();
+        }
+
+        private void ComputeDecibel(float[] waveform)
+        {
+            int frame_sample_length = (int)(_vad_opts.frame_length_ms * _vad_opts.sample_rate / 1000);
+            int frame_shift_length = (int)(_vad_opts.frame_in_ms * _vad_opts.sample_rate / 1000);
+            if (_data_buf_all_size == 0)
+            {
+                _data_buf_all_size = waveform.Length;
+                _data_buf_size = _data_buf_all_size;
+            }
+            else
+            {
+                _data_buf_all_size += waveform.Length;
+            }
+
+            for (int offset = 0; offset < waveform.Length - frame_sample_length + 1; offset += frame_shift_length)
+            {
+                float[] _waveform_chunk = new float[frame_sample_length];
+                Array.Copy(waveform, offset, _waveform_chunk, 0, _waveform_chunk.Length);
+                float[] _waveform_chunk_pow = _waveform_chunk.Select(x => (float)Math.Pow((double)x, 2)).ToArray();
+                _decibel.Add(
+                    10 * Math.Log10(
+                        _waveform_chunk_pow.Sum() + 0.000001
+                        )
+                    );
+            }
+
+        }
+
+        private void ComputeScores(float[,,] scores)
+        {
+            _vad_opts.nn_eval_block_size = scores.GetLength(1);
+            _frm_cnt += scores.GetLength(1);
+            _scores = scores;
+        }
+
+        private void PopDataBufTillFrame(int frame_idx)// need check again
+        {
+            while (_data_buf_start_frame < frame_idx)
+            {
+                if (_data_buf_size >= (int)(_vad_opts.frame_in_ms * _vad_opts.sample_rate / 1000))
+                {
+                    _data_buf_start_frame += 1;
+                    _data_buf_size = _data_buf_all_size - _data_buf_start_frame * (int)(_vad_opts.frame_in_ms * _vad_opts.sample_rate / 1000);
+                }
+            }
+        }
+
+        private void PopDataToOutputBuf(int start_frm, int frm_cnt, bool first_frm_is_start_point,
+                       bool last_frm_is_end_point, bool end_point_is_sent_end)
+        {
+            PopDataBufTillFrame(start_frm);
+            int expected_sample_number = (int)(frm_cnt * _vad_opts.sample_rate * _vad_opts.frame_in_ms / 1000);
+            if (last_frm_is_end_point)
+            {
+                int extra_sample = Math.Max(0, (int)(_vad_opts.frame_length_ms * _vad_opts.sample_rate / 1000 - _vad_opts.sample_rate * _vad_opts.frame_in_ms / 1000));
+                expected_sample_number += (int)(extra_sample);
+            }
+
+            if (end_point_is_sent_end)
+            {
+                expected_sample_number = Math.Max(expected_sample_number, _data_buf_size);
+            }
+            if (_data_buf_size < expected_sample_number)
+            {
+                Console.WriteLine("error in calling pop data_buf\n");
+            }
+
+            if (_output_data_buf.Count == 0 || first_frm_is_start_point)
+            {
+                _output_data_buf.Add(new E2EVadSpeechBufWithDoaEntity());
+                _output_data_buf.Last().Reset();
+                _output_data_buf.Last().start_ms = start_frm * _vad_opts.frame_in_ms;
+                _output_data_buf.Last().end_ms = _output_data_buf.Last().start_ms;
+                _output_data_buf.Last().doa = 0;
+            }
+
+            E2EVadSpeechBufWithDoaEntity cur_seg = _output_data_buf.Last();
+            if (cur_seg.end_ms != start_frm * _vad_opts.frame_in_ms)
+            {
+                Console.WriteLine("warning\n");
+            }
+
+            int out_pos = cur_seg.buffer.Length;  // cur_seg.buff现在没做任何操作
+            int data_to_pop = 0;
+            if (end_point_is_sent_end)
+            {
+                data_to_pop = expected_sample_number;
+            }
+            else
+            {
+                data_to_pop = (int)(frm_cnt * _vad_opts.frame_in_ms * _vad_opts.sample_rate / 1000);
+            }
+            if (data_to_pop > _data_buf_size)
+            {
+                Console.WriteLine("VAD data_to_pop is bigger than _data_buf_size!!!\n");
+                data_to_pop = _data_buf_size;
+                expected_sample_number = _data_buf_size;
+            }
+
+
+            cur_seg.doa = 0;
+            for (int sample_cpy_out = 0; sample_cpy_out < data_to_pop; sample_cpy_out++)
+            {
+                out_pos += 1;
+            }
+            for (int sample_cpy_out = data_to_pop; sample_cpy_out < expected_sample_number; sample_cpy_out++)
+            {
+                out_pos += 1;
+            }
+
+            if (cur_seg.end_ms != start_frm * _vad_opts.frame_in_ms)
+            {
+                Console.WriteLine("Something wrong with the VAD algorithm\n");
+            }
+
+            _data_buf_start_frame += frm_cnt;
+            cur_seg.end_ms = (start_frm + frm_cnt) * _vad_opts.frame_in_ms;
+            if (first_frm_is_start_point)
+            {
+                cur_seg.contain_seg_start_point = true;
+            }
+
+            if (last_frm_is_end_point)
+            {
+                cur_seg.contain_seg_end_point = true;
+            }
+        }
+
+        private void OnSilenceDetected(int valid_frame)
+        {
+            _lastest_confirmed_silence_frame = valid_frame;
+            if (_vad_state_machine == (int)VadStateMachine.kVadInStateStartPointNotDetected)
+            {
+                PopDataBufTillFrame(valid_frame);
+            }
+
+        }
+
+        private void OnVoiceDetected(int valid_frame)
+        {
+            _latest_confirmed_speech_frame = valid_frame;
+            PopDataToOutputBuf(valid_frame, 1, false, false, false);
+        }
+
+        private void OnVoiceStart(int start_frame, bool fake_result = false)
+        {
+            if (_vad_opts.do_start_point_detection)
+            {
+                //do nothing
+            }
+            if (_confirmed_start_frame != -1)
+            {
+
+                Console.WriteLine("not reset vad properly\n");
+            }
+            else
+            {
+                _confirmed_start_frame = start_frame;
+            }
+            if (!fake_result || _vad_state_machine == (int)VadStateMachine.kVadInStateStartPointNotDetected)
+            {
+
+                PopDataToOutputBuf(_confirmed_start_frame, 1, true, false, false);
+            }
+        }
+
+        private void OnVoiceEnd(int end_frame, bool fake_result, bool is_last_frame)
+        {
+            for (int t = _latest_confirmed_speech_frame + 1; t < end_frame; t++)
+            {
+                OnVoiceDetected(t);
+            }
+            if (_vad_opts.do_end_point_detection)
+            {
+                //do nothing
+            }
+            if (_confirmed_end_frame != -1)
+            {
+                Console.WriteLine("not reset vad properly\n");
+            }
+            else
+            {
+                _confirmed_end_frame = end_frame;
+            }
+            if (!fake_result)
+            {
+                _sil_frame = 0;
+                PopDataToOutputBuf(_confirmed_end_frame, 1, false, true, is_last_frame);
+            }
+            _number_end_time_detected += 1;
+        }
+
+        private void MaybeOnVoiceEndIfLastFrame(bool is_final_frame, int cur_frm_idx)
+        {
+            if (is_final_frame)
+            {
+                OnVoiceEnd(cur_frm_idx, false, true);
+                _vad_state_machine = (int)VadStateMachine.kVadInStateEndPointDetected;
+            }
+        }
+
+        private int GetLatency()
+        {
+            return (int)(LatencyFrmNumAtStartPoint() * _vad_opts.frame_in_ms);
+        }
+
+        private int LatencyFrmNumAtStartPoint()
+        {
+            int vad_latency = _windows_detector.GetWinSize();
+            if (_vad_opts.do_extend != 0)
+            {
+                vad_latency += (int)(_vad_opts.lookback_time_start_point / _vad_opts.frame_in_ms);
+            }
+            return vad_latency;
+        }
+
+        private FrameState GetFrameState(int t)
+        {
+
+            FrameState frame_state = FrameState.kFrameStateInvalid;
+            double cur_decibel = _decibel[t];
+            double cur_snr = cur_decibel - _noise_average_decibel;
+            if (cur_decibel < _vad_opts.decibel_thres)
+            {
+                frame_state = FrameState.kFrameStateSil;
+                DetectOneFrame(frame_state, t, false);
+                return frame_state;
+            }
+
+
+            double sum_score = 0.0D;
+            double noise_prob = 0.0D;
+            Trace.Assert(_sil_pdf_ids.Length == _vad_opts.silence_pdf_num, "");
+            if (_sil_pdf_ids.Length > 0)
+            {
+                Trace.Assert(_scores.GetLength(0) == 1, "只支持batch_size = 1的测试");  // 只支持batch_size = 1的测试
+                float[] sil_pdf_scores = new float[_sil_pdf_ids.Length];
+                int j = 0;
+                foreach (int sil_pdf_id in _sil_pdf_ids)
+                {
+                    sil_pdf_scores[j] = _scores[0,t - _idx_pre_chunk,sil_pdf_id];
+                    j++;
+                }
+                sum_score = sil_pdf_scores.Length == 0 ? 0 : sil_pdf_scores.Sum();
+                noise_prob = Math.Log(sum_score) * _vad_opts.speech_2_noise_ratio;
+                double total_score = 1.0D;
+                sum_score = total_score - sum_score;
+            }
+            double speech_prob = Math.Log(sum_score);
+            if (_vad_opts.output_frame_probs)
+            {
+                E2EVadFrameProbEntity frame_prob = new E2EVadFrameProbEntity();
+                frame_prob.noise_prob = noise_prob;
+                frame_prob.speech_prob = speech_prob;
+                frame_prob.score = sum_score;
+                frame_prob.frame_id = t;
+                _frame_probs.Add(frame_prob);
+            }
+
+            if (Math.Exp(speech_prob) >= Math.Exp(noise_prob) + _speech_noise_thres)
+            {
+                if (cur_snr >= _vad_opts.snr_thres && cur_decibel >= _vad_opts.decibel_thres)
+                {
+                    frame_state = FrameState.kFrameStateSpeech;
+                }
+                else
+                {
+                    frame_state = FrameState.kFrameStateSil;
+                }
+            }
+            else
+            {
+                frame_state = FrameState.kFrameStateSil;
+                if (_noise_average_decibel < -99.9)
+                {
+                    _noise_average_decibel = cur_decibel;
+                }
+                else
+                {
+                    _noise_average_decibel = (cur_decibel + _noise_average_decibel * (_vad_opts.noise_frame_num_used_for_snr - 1)) / _vad_opts.noise_frame_num_used_for_snr;
+                }
+            }
+            return frame_state;
+        }
+
+        public SegmentEntity[] DefaultCall(float[,,] score, float[] waveform,
+            bool is_final = false, int max_end_sil = 800, bool online = false
+            )
+        {
+            _max_end_sil_frame_cnt_thresh = max_end_sil - _vad_opts.speech_to_sil_time_thres;
+            // compute decibel for each frame
+            ComputeDecibel(waveform);
+            ComputeScores(score);
+            if (!is_final)
+            {
+                DetectCommonFrames();
+            }
+            else
+            {
+                DetectLastFrames();
+            }
+            int batchSize = score.GetLength(0);
+            SegmentEntity[] segments = new SegmentEntity[batchSize];
+            for (int batch_num = 0; batch_num < batchSize; batch_num++) // only support batch_size = 1 now
+            {
+                List<int[]> segment_batch = new List<int[]>();
+                if (_output_data_buf.Count > 0)
+                {
+                    for (int i = _output_data_buf_offset; i < _output_data_buf.Count; i++)
+                    {
+                        int start_ms;
+                        int end_ms;
+                        if (online)
+                        {
+                            if (!_output_data_buf[i].contain_seg_start_point)
+                            {
+                                continue;
+                            }
+                            if (!_next_seg && !_output_data_buf[i].contain_seg_end_point)
+                            {
+                                continue;
+                            }
+                            start_ms = _next_seg ? _output_data_buf[i].start_ms : -1;
+                            if (_output_data_buf[i].contain_seg_end_point)
+                            {
+                                end_ms = _output_data_buf[i].end_ms;
+                                _next_seg = true;
+                                _output_data_buf_offset += 1;
+                            }
+                            else
+                            {
+                                end_ms = -1;
+                                _next_seg = false;
+                            }
+                        }
+                        else
+                        {
+                            if (!is_final && (!_output_data_buf[i].contain_seg_start_point || !_output_data_buf[i].contain_seg_end_point))
+                            {
+                                continue;
+                            }
+                            start_ms = _output_data_buf[i].start_ms;
+                            end_ms = _output_data_buf[i].end_ms;
+                            _output_data_buf_offset += 1;
+
+                        }
+                        int[] segment_ms = new int[] { start_ms, end_ms };
+                        segment_batch.Add(segment_ms);
+                        
+                    }
+
+                }
+
+                if (segment_batch.Count > 0)
+                {
+                    if (segments[batch_num] == null)
+                    {
+                        segments[batch_num] = new SegmentEntity();
+                    }
+                    segments[batch_num].Segment.AddRange(segment_batch);
+                }
+            }
+
+            if (is_final)
+            {
+                // reset class variables and clear the dict for the next query
+                AllResetDetection();
+            }
+
+            return segments;
+        }
+
+        private int DetectCommonFrames()
+        {
+            if (_vad_state_machine == (int)VadStateMachine.kVadInStateEndPointDetected)
+            {
+                return 0;
+            }
+            for (int i = _vad_opts.nn_eval_block_size - 1; i > -1; i += -1)
+            {
+                FrameState frame_state = FrameState.kFrameStateInvalid;
+                frame_state = GetFrameState(_frm_cnt - 1 - i);
+                DetectOneFrame(frame_state, _frm_cnt - 1 - i, false);
+            }
+
+            _idx_pre_chunk += _scores.GetLength(1)* _scores.GetLength(0); //_scores.shape[1];
+            return 0;
+        }
+
+        private int DetectLastFrames()
+        {
+            if (_vad_state_machine == (int)VadStateMachine.kVadInStateEndPointDetected)
+            {
+                return 0;
+            }
+            for (int i = _vad_opts.nn_eval_block_size - 1; i > -1; i += -1)
+            {
+                FrameState frame_state = FrameState.kFrameStateInvalid;
+                frame_state = GetFrameState(_frm_cnt - 1 - i);
+                if (i != 0)
+                {
+                    DetectOneFrame(frame_state, _frm_cnt - 1 - i, false);
+                }
+                else
+                {
+                    DetectOneFrame(frame_state, _frm_cnt - 1, true);
+                }
+
+
+            }
+
+            return 0;
+        }
+
+        private void DetectOneFrame(FrameState cur_frm_state, int cur_frm_idx, bool is_final_frame)
+        {
+            FrameState tmp_cur_frm_state = FrameState.kFrameStateInvalid;
+            if (cur_frm_state == FrameState.kFrameStateSpeech)
+            {
+                if (Math.Abs(1.0) > _vad_opts.fe_prior_thres)//Fabs
+                {
+                    tmp_cur_frm_state = FrameState.kFrameStateSpeech;
+                }
+                else
+                {
+                    tmp_cur_frm_state = FrameState.kFrameStateSil;
+                }
+            }
+            else if (cur_frm_state == FrameState.kFrameStateSil)
+            {
+                tmp_cur_frm_state = FrameState.kFrameStateSil;
+            }
+
+            AudioChangeState state_change = _windows_detector.DetectOneFrame(tmp_cur_frm_state, cur_frm_idx);
+            int frm_shift_in_ms = _vad_opts.frame_in_ms;
+            if (AudioChangeState.kChangeStateSil2Speech == state_change)
+            {
+                int silence_frame_count = _continous_silence_frame_count; // no used
+                _continous_silence_frame_count = 0;
+                _pre_end_silence_detected = false;
+                int start_frame = 0;
+                if (_vad_state_machine == (int)VadStateMachine.kVadInStateStartPointNotDetected)
+                {
+                    start_frame = Math.Max(_data_buf_start_frame, cur_frm_idx - LatencyFrmNumAtStartPoint());
+                    OnVoiceStart(start_frame);
+                    _vad_state_machine = (int)VadStateMachine.kVadInStateInSpeechSegment;
+                    for (int t = start_frame + 1; t < cur_frm_idx + 1; t++)
+                    {
+                        OnVoiceDetected(t);
+                    }
+
+                }
+                else if (_vad_state_machine == (int)VadStateMachine.kVadInStateInSpeechSegment)
+                {
+                    for (int t = _latest_confirmed_speech_frame + 1; t < cur_frm_idx; t++)
+                    {
+                        OnVoiceDetected(t);
+                    }
+                    if (cur_frm_idx - _confirmed_start_frame + 1 > _vad_opts.max_single_segment_time / frm_shift_in_ms)
+                    {
+                        OnVoiceEnd(cur_frm_idx, false, false);
+                        _vad_state_machine = (int)VadStateMachine.kVadInStateEndPointDetected;
+                    }
+
+                    else if (!is_final_frame)
+                    {
+                        OnVoiceDetected(cur_frm_idx);
+                    }
+                    else
+                    {
+                        MaybeOnVoiceEndIfLastFrame(is_final_frame, cur_frm_idx);
+                    }
+
+                }
+                else
+                {
+                    return;
+                }
+            }
+            else if (AudioChangeState.kChangeStateSpeech2Sil == state_change)
+            {
+                _continous_silence_frame_count = 0;
+                if (_vad_state_machine == (int)VadStateMachine.kVadInStateStartPointNotDetected)
+                { return; }
+                else if (_vad_state_machine == (int)VadStateMachine.kVadInStateInSpeechSegment)
+                {
+                    if (cur_frm_idx - _confirmed_start_frame + 1 > _vad_opts.max_single_segment_time / frm_shift_in_ms)
+                    {
+                        OnVoiceEnd(cur_frm_idx, false, false);
+                        _vad_state_machine = (int)VadStateMachine.kVadInStateEndPointDetected;
+                    }
+                    else if (!is_final_frame)
+                    {
+                        OnVoiceDetected(cur_frm_idx);
+                    }
+                    else
+                    {
+                        MaybeOnVoiceEndIfLastFrame(is_final_frame, cur_frm_idx);
+                    }
+
+                }
+                else
+                {
+                    return;
+                }
+            }
+            else if (AudioChangeState.kChangeStateSpeech2Speech == state_change)
+            {
+                _continous_silence_frame_count = 0;
+                if (_vad_state_machine == (int)VadStateMachine.kVadInStateInSpeechSegment)
+                {
+                    if (cur_frm_idx - _confirmed_start_frame + 1 > _vad_opts.max_single_segment_time / frm_shift_in_ms)
+                    {
+                        _max_time_out = true;
+                        OnVoiceEnd(cur_frm_idx, false, false);
+                        _vad_state_machine = (int)VadStateMachine.kVadInStateEndPointDetected;
+                    }
+                    else if (!is_final_frame)
+                    {
+                        OnVoiceDetected(cur_frm_idx);
+                    }
+                    else
+                    {
+                        MaybeOnVoiceEndIfLastFrame(is_final_frame, cur_frm_idx);
+                    }
+                }
+                else
+                {
+                    return;
+                }
+
+            }
+            else if (AudioChangeState.kChangeStateSil2Sil == state_change)
+            {
+                _continous_silence_frame_count += 1;
+                if (_vad_state_machine == (int)VadStateMachine.kVadInStateStartPointNotDetected)
+                {
+                    // silence timeout, return zero length decision
+                    if (((_vad_opts.detect_mode == (int)VadDetectMode.kVadSingleUtteranceDetectMode) && (
+                            _continous_silence_frame_count * frm_shift_in_ms > _vad_opts.max_start_silence_time)) || (is_final_frame && _number_end_time_detected == 0))
+                    {
+                        for (int t = _lastest_confirmed_silence_frame + 1; t < cur_frm_idx; t++)
+                        {
+                            OnSilenceDetected(t);
+                        }
+                        OnVoiceStart(0, true);
+                        OnVoiceEnd(0, true, false);
+                        _vad_state_machine = (int)VadStateMachine.kVadInStateEndPointDetected;
+                    }
+                    else
+                    {
+                        if (cur_frm_idx >= LatencyFrmNumAtStartPoint())
+                        {
+                            OnSilenceDetected(cur_frm_idx - LatencyFrmNumAtStartPoint());
+                        }
+                    }
+                }
+                else if (_vad_state_machine == (int)VadStateMachine.kVadInStateInSpeechSegment)
+                {
+                    if (_continous_silence_frame_count * frm_shift_in_ms >= _max_end_sil_frame_cnt_thresh)
+                    {
+                        int lookback_frame = (int)(_max_end_sil_frame_cnt_thresh / frm_shift_in_ms);
+                        if (_vad_opts.do_extend != 0)
+                        {
+                            lookback_frame -= (int)(_vad_opts.lookahead_time_end_point / frm_shift_in_ms);
+                            lookback_frame -= 1;
+                            lookback_frame = Math.Max(0, lookback_frame);
+                        }
+
+                        OnVoiceEnd(cur_frm_idx - lookback_frame, false, false);
+                        _vad_state_machine = (int)VadStateMachine.kVadInStateEndPointDetected;
+                    }
+                    else if (cur_frm_idx - _confirmed_start_frame + 1 > _vad_opts.max_single_segment_time / frm_shift_in_ms)
+                    {
+                        OnVoiceEnd(cur_frm_idx, false, false);
+                        _vad_state_machine = (int)VadStateMachine.kVadInStateEndPointDetected;
+                    }
+
+                    else if (_vad_opts.do_extend != 0 && !is_final_frame)
+                    {
+                        if (_continous_silence_frame_count <= (int)(_vad_opts.lookahead_time_end_point / frm_shift_in_ms))
+                        {
+                            OnVoiceDetected(cur_frm_idx);
+                        }
+                    }
+
+                    else
+                    {
+                        MaybeOnVoiceEndIfLastFrame(is_final_frame, cur_frm_idx);
+                    }
+                }
+                else
+                {
+                    return;
+                }
+
+            }
+
+            if (_vad_state_machine == (int)VadStateMachine.kVadInStateEndPointDetected && _vad_opts.detect_mode == (int)VadDetectMode.kVadMutipleUtteranceDetectMode)
+            {
+                ResetDetection();
+            }
+
+        }
+
+    }
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/Lib/kaldi-native-fbank-dll.dll b/funasr/runtime/csharp/AliFsmnVadSharp/Lib/kaldi-native-fbank-dll.dll
new file mode 100644
index 0000000000000000000000000000000000000000..cddc94074c05f4d5c8d30fc84e71c660e8d64183
GIT binary patch
literal 487936
zcmeFa349bq6E?nq1Q#?Us8K|PsGt$#P&|kS1Wa^Mf~cV2fhdUK6d@oUT!z)ebr6*(
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literal 0
HcmV?d00001

diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/Model/CmvnEntity.cs b/funasr/runtime/csharp/AliFsmnVadSharp/Model/CmvnEntity.cs
new file mode 100644
index 000000000..2f93df1b2
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/Model/CmvnEntity.cs
@@ -0,0 +1,17 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+
+namespace AliFsmnVadSharp.Model
+{
+    internal class CmvnEntity
+    {
+        private List<float> _means = new List<float>();
+        private List<float> _vars = new List<float>();
+
+        public List<float> Means { get => _means; set => _means = value; }
+        public List<float> Vars { get => _vars; set => _vars = value; }
+    }
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/Model/E2EVadFrameProbEntity.cs b/funasr/runtime/csharp/AliFsmnVadSharp/Model/E2EVadFrameProbEntity.cs
new file mode 100644
index 000000000..58a4ca9a0
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/Model/E2EVadFrameProbEntity.cs
@@ -0,0 +1,23 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+
+namespace AliFsmnVadSharp.Model
+{
+    internal class E2EVadFrameProbEntity
+    {
+        private double _noise_prob = 0.0F;
+        private double _speech_prob = 0.0F;
+        private double _score = 0.0F;
+        private int _frame_id = 0;
+        private int _frm_state = 0;
+
+        public double noise_prob { get => _noise_prob; set => _noise_prob = value; }
+        public double speech_prob { get => _speech_prob; set => _speech_prob = value; }
+        public double score { get => _score; set => _score = value; }
+        public int frame_id { get => _frame_id; set => _frame_id = value; }
+        public int frm_state { get => _frm_state; set => _frm_state = value; }
+    }
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/Model/E2EVadSpeechBufWithDoaEntity.cs b/funasr/runtime/csharp/AliFsmnVadSharp/Model/E2EVadSpeechBufWithDoaEntity.cs
new file mode 100644
index 000000000..8c2e7f7a9
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/Model/E2EVadSpeechBufWithDoaEntity.cs
@@ -0,0 +1,98 @@
+// AliFsmnVadSharp, Version=1.0.0.0, Culture=neutral, PublicKeyToken=null
+// AliFsmnVadSharp.Model.E2EVadSpeechBufWithDoaEntity
+internal class E2EVadSpeechBufWithDoaEntity
+{
+	private int _start_ms = 0;
+
+	private int _end_ms = 0;
+
+	private byte[]? _buffer;
+
+	private bool _contain_seg_start_point = false;
+
+	private bool _contain_seg_end_point = false;
+
+	private int _doa = 0;
+
+	public int start_ms
+	{
+		get
+		{
+			return _start_ms;
+		}
+		set
+		{
+			_start_ms = value;
+		}
+	}
+
+	public int end_ms
+	{
+		get
+		{
+			return _end_ms;
+		}
+		set
+		{
+			_end_ms = value;
+		}
+	}
+
+	public byte[]? buffer
+	{
+		get
+		{
+			return _buffer;
+		}
+		set
+		{
+			_buffer = value;
+		}
+	}
+
+	public bool contain_seg_start_point
+	{
+		get
+		{
+			return _contain_seg_start_point;
+		}
+		set
+		{
+			_contain_seg_start_point = value;
+		}
+	}
+
+	public bool contain_seg_end_point
+	{
+		get
+		{
+			return _contain_seg_end_point;
+		}
+		set
+		{
+			_contain_seg_end_point = value;
+		}
+	}
+
+	public int doa
+	{
+		get
+		{
+			return _doa;
+		}
+		set
+		{
+			_doa = value;
+		}
+	}
+
+	public void Reset()
+	{
+		_start_ms = 0;
+		_end_ms = 0;
+		_buffer = new byte[0];
+		_contain_seg_start_point = false;
+		_contain_seg_end_point = false;
+		_doa = 0;
+	}
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/Model/EncoderConfEntity.cs b/funasr/runtime/csharp/AliFsmnVadSharp/Model/EncoderConfEntity.cs
new file mode 100644
index 000000000..8365b1206
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/Model/EncoderConfEntity.cs
@@ -0,0 +1,35 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+
+namespace AliFsmnVadSharp.Model
+{
+    public class EncoderConfEntity
+    {
+        private int _input_dim=400;
+        private int _input_affineDim = 140;
+        private int _fsmn_layers = 4;
+        private int _linear_dim = 250;
+        private int _proj_dim = 128;
+        private int _lorder = 20;
+        private int _rorder = 0;
+        private int _lstride = 1;
+        private int _rstride = 0;
+        private int _output_dffine_dim = 140;
+        private int _output_dim = 248;
+
+        public int input_dim { get => _input_dim; set => _input_dim = value; }
+        public int input_affine_dim { get => _input_affineDim; set => _input_affineDim = value; }
+        public int fsmn_layers { get => _fsmn_layers; set => _fsmn_layers = value; }
+        public int linear_dim { get => _linear_dim; set => _linear_dim = value; }
+        public int proj_dim { get => _proj_dim; set => _proj_dim = value; }
+        public int lorder { get => _lorder; set => _lorder = value; }
+        public int rorder { get => _rorder; set => _rorder = value; }
+        public int lstride { get => _lstride; set => _lstride = value; }
+        public int rstride { get => _rstride; set => _rstride = value; }
+        public int output_affine_dim { get => _output_dffine_dim; set => _output_dffine_dim = value; }
+        public int output_dim { get => _output_dim; set => _output_dim = value; }
+    }
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/Model/FrontendConfEntity.cs b/funasr/runtime/csharp/AliFsmnVadSharp/Model/FrontendConfEntity.cs
new file mode 100644
index 000000000..22bb35aed
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/Model/FrontendConfEntity.cs
@@ -0,0 +1,29 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+
+namespace AliFsmnVadSharp.Model
+{
+    public class FrontendConfEntity
+    {
+        private int _fs = 16000;
+        private string _window = "hamming";
+        private int _n_mels = 80;
+        private int _frame_length = 25;
+        private int _frame_shift = 10;
+        private float _dither = 0.0F;
+        private int _lfr_m = 5;
+        private int _lfr_n = 1;
+
+        public int fs { get => _fs; set => _fs = value; }
+        public string window { get => _window; set => _window = value; }
+        public int n_mels { get => _n_mels; set => _n_mels = value; }
+        public int frame_length { get => _frame_length; set => _frame_length = value; }
+        public int frame_shift { get => _frame_shift; set => _frame_shift = value; }
+        public float dither { get => _dither; set => _dither = value; }
+        public int lfr_m { get => _lfr_m; set => _lfr_m = value; }
+        public int lfr_n { get => _lfr_n; set => _lfr_n = value; }
+    }
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/Model/SegmentEntity.cs b/funasr/runtime/csharp/AliFsmnVadSharp/Model/SegmentEntity.cs
new file mode 100644
index 000000000..bdb715d8d
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/Model/SegmentEntity.cs
@@ -0,0 +1,22 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+
+namespace AliFsmnVadSharp.Model
+{
+    public class SegmentEntity
+    {
+        private List<int[]> _segment=new List<int[]>();
+        private List<float[]> _waveform=new List<float[]>();
+
+        public List<int[]> Segment { get => _segment; set => _segment = value; }
+        public List<float[]> Waveform { get => _waveform; set => _waveform = value; }
+        //public SegmentEntity()
+        //{
+        //    int[] t=new int[0];
+        //    _segment.Add(t);
+        //}
+    }
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/Model/VadInputEntity.cs b/funasr/runtime/csharp/AliFsmnVadSharp/Model/VadInputEntity.cs
new file mode 100644
index 000000000..fcd63d892
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/Model/VadInputEntity.cs
@@ -0,0 +1,23 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+
+namespace AliFsmnVadSharp.Model
+{
+    internal class VadInputEntity
+    {
+        private float[]? _speech;
+        private int _speechLength;
+        private List<float[]> _inCaches = new List<float[]>();
+        private float[]? _waveform;
+        private E2EVadModel _vad_scorer;
+
+        public float[]? Speech { get => _speech; set => _speech = value; }
+        public int SpeechLength { get => _speechLength; set => _speechLength = value; }
+        public List<float[]> InCaches { get => _inCaches; set => _inCaches = value; }
+        public float[] Waveform { get => _waveform; set => _waveform = value; }
+        internal E2EVadModel VadScorer { get => _vad_scorer; set => _vad_scorer = value; }
+    }
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/Model/VadOutputEntity.cs b/funasr/runtime/csharp/AliFsmnVadSharp/Model/VadOutputEntity.cs
new file mode 100644
index 000000000..fa8639e61
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/Model/VadOutputEntity.cs
@@ -0,0 +1,19 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+
+namespace AliFsmnVadSharp.Model
+{
+    internal class VadOutputEntity
+    {
+        private float[,,]? _scores;
+        private List<float[]> _outCaches=new List<float[]>();
+        private float[]? _waveform;
+
+        public float[,,]? Scores { get => _scores; set => _scores = value; }
+        public List<float[]> OutCaches { get => _outCaches; set => _outCaches = value; }
+        public float[] Waveform { get => _waveform; set => _waveform = value; }
+    }
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/Model/VadPostConfEntity.cs b/funasr/runtime/csharp/AliFsmnVadSharp/Model/VadPostConfEntity.cs
new file mode 100644
index 000000000..e566cf2b1
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/Model/VadPostConfEntity.cs
@@ -0,0 +1,72 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+
+namespace AliFsmnVadSharp.Model
+{
+    public class VadPostConfEntity
+    {
+        private int _sample_rate= 16000;
+        private int _detect_mode = 1 ;
+        private int _snr_mode = 0;
+        private int _max_end_silence_time = 800;
+        private int _max_start_silence_time = 3000;
+        private bool _do_start_point_detection = true;
+        private bool _do_end_point_detection = true;
+        private int _window_size_ms = 200;
+        private int _sil_to_speech_time_thres = 150;
+        private int _speech_to_sil_time_thres = 150;
+        private float _speech_2_noise_ratio = 1.0F;
+        private int _do_extend = 1;
+        private int _lookback_time_start_point = 200;
+        private int _lookahead_time_end_point = 100;
+        private int _max_single_segment_time = 60000;
+        private int _nn_eval_block_size = 8;
+        private int _dcd_block_size = 4;
+        private float _snr_thres = -100.0F;
+        private int _noise_frame_num_used_for_snr = 100;
+        private float _decibel_thres = -100.0F;
+        private float _speech_noise_thres = 0.6F;
+        private float _fe_prior_thres = 0.0001F;
+        private int _silence_pdf_num = 1;
+        private int[] _sil_pdf_ids = new int[] {0};
+        private float _speech_noise_thresh_low = -0.1F;
+        private float _speech_noise_thresh_high = 0.3F;
+        private bool _output_frame_probs = false;
+        private int _frame_in_ms = 10;
+        private int _frame_length_ms = 25;
+
+        public int sample_rate { get => _sample_rate; set => _sample_rate = value; }
+        public int detect_mode { get => _detect_mode; set => _detect_mode = value; }
+        public int snr_mode { get => _snr_mode; set => _snr_mode = value; }
+        public int max_end_silence_time { get => _max_end_silence_time; set => _max_end_silence_time = value; }
+        public int max_start_silence_time { get => _max_start_silence_time; set => _max_start_silence_time = value; }
+        public bool do_start_point_detection { get => _do_start_point_detection; set => _do_start_point_detection = value; }
+        public bool do_end_point_detection { get => _do_end_point_detection; set => _do_end_point_detection = value; }
+        public int window_size_ms { get => _window_size_ms; set => _window_size_ms = value; }
+        public int sil_to_speech_time_thres { get => _sil_to_speech_time_thres; set => _sil_to_speech_time_thres = value; }
+        public int speech_to_sil_time_thres { get => _speech_to_sil_time_thres; set => _speech_to_sil_time_thres = value; }
+        public float speech_2_noise_ratio { get => _speech_2_noise_ratio; set => _speech_2_noise_ratio = value; }
+        public int do_extend { get => _do_extend; set => _do_extend = value; }
+        public int lookback_time_start_point { get => _lookback_time_start_point; set => _lookback_time_start_point = value; }
+        public int lookahead_time_end_point { get => _lookahead_time_end_point; set => _lookahead_time_end_point = value; }
+        public int max_single_segment_time { get => _max_single_segment_time; set => _max_single_segment_time = value; }
+        public int nn_eval_block_size { get => _nn_eval_block_size; set => _nn_eval_block_size = value; }
+        public int dcd_block_size { get => _dcd_block_size; set => _dcd_block_size = value; }
+        public float snr_thres { get => _snr_thres; set => _snr_thres = value; }
+        public int noise_frame_num_used_for_snr { get => _noise_frame_num_used_for_snr; set => _noise_frame_num_used_for_snr = value; }
+        public float decibel_thres { get => _decibel_thres; set => _decibel_thres = value; }
+        public float speech_noise_thres { get => _speech_noise_thres; set => _speech_noise_thres = value; }
+        public float fe_prior_thres { get => _fe_prior_thres; set => _fe_prior_thres = value; }
+        public int silence_pdf_num { get => _silence_pdf_num; set => _silence_pdf_num = value; }
+        public int[] sil_pdf_ids { get => _sil_pdf_ids; set => _sil_pdf_ids = value; }
+        public float speech_noise_thresh_low { get => _speech_noise_thresh_low; set => _speech_noise_thresh_low = value; }
+        public float speech_noise_thresh_high { get => _speech_noise_thresh_high; set => _speech_noise_thresh_high = value; }
+        public bool output_frame_probs { get => _output_frame_probs; set => _output_frame_probs = value; }
+        public int frame_in_ms { get => _frame_in_ms; set => _frame_in_ms = value; }
+        public int frame_length_ms { get => _frame_length_ms; set => _frame_length_ms = value; }
+        
+    }
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/Model/VadYamlEntity.cs b/funasr/runtime/csharp/AliFsmnVadSharp/Model/VadYamlEntity.cs
new file mode 100644
index 000000000..65e77eda8
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/Model/VadYamlEntity.cs
@@ -0,0 +1,27 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+
+namespace AliFsmnVadSharp.Model
+{
+    internal class VadYamlEntity
+    {
+        private int _input_size;
+        private string _frontend = "wav_frontend";
+        private FrontendConfEntity _frontend_conf=new FrontendConfEntity();
+        private string _model = "e2evad";
+        private string _encoder = "fsmn";
+        private EncoderConfEntity _encoder_conf=new EncoderConfEntity();
+        private VadPostConfEntity _vad_post_conf=new VadPostConfEntity();
+
+        public int input_size { get => _input_size; set => _input_size = value; }
+        public string frontend { get => _frontend; set => _frontend = value; }
+        public string model { get => _model; set => _model = value; }
+        public string encoder { get => _encoder; set => _encoder = value; }
+        public FrontendConfEntity frontend_conf { get => _frontend_conf; set => _frontend_conf = value; }
+        public EncoderConfEntity encoder_conf { get => _encoder_conf; set => _encoder_conf = value; }
+        public VadPostConfEntity vad_post_conf { get => _vad_post_conf; set => _vad_post_conf = value; }
+    }
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/Struct/FbankData.cs b/funasr/runtime/csharp/AliFsmnVadSharp/Struct/FbankData.cs
new file mode 100644
index 000000000..bbad3dc95
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/Struct/FbankData.cs
@@ -0,0 +1,6 @@
+using System.Runtime.InteropServices;
+
+namespace AliFsmnVadSharp.Struct
+{
+    
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/Utils/YamlHelper.cs b/funasr/runtime/csharp/AliFsmnVadSharp/Utils/YamlHelper.cs
new file mode 100644
index 000000000..0b460ff16
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/Utils/YamlHelper.cs
@@ -0,0 +1,28 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+using System.Text.Json;
+using YamlDotNet.Serialization;
+
+namespace AliFsmnVadSharp.Utils
+{
+    internal class YamlHelper
+    {
+        public static T ReadYaml<T>(string yamlFilePath)
+        {
+            if (!File.Exists(yamlFilePath))
+            {
+#pragma warning disable CS8603 // 可能返回 null 引用。
+                return default(T);
+#pragma warning restore CS8603 // 可能返回 null 引用。
+            }
+            StreamReader yamlReader = File.OpenText(yamlFilePath);
+            Deserializer yamlDeserializer = new Deserializer();
+            T info = yamlDeserializer.Deserialize<T>(yamlReader);
+            yamlReader.Close();
+            return info;
+        }
+    }
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/WavFrontend.cs b/funasr/runtime/csharp/AliFsmnVadSharp/WavFrontend.cs
new file mode 100644
index 000000000..2c5b50fbb
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/WavFrontend.cs
@@ -0,0 +1,185 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+using AliFsmnVadSharp.Model;
+using AliFsmnVadSharp.DLL;
+using AliFsmnVadSharp.Struct;
+using System.Runtime.InteropServices;
+
+namespace AliFsmnVadSharp
+{
+    internal class WavFrontend
+    {
+        private string _mvnFilePath;
+        private FrontendConfEntity _frontendConfEntity;
+        IntPtr _opts = IntPtr.Zero;
+        private CmvnEntity _cmvnEntity;
+
+        private static int _fbank_beg_idx = 0;
+
+        public WavFrontend(string mvnFilePath, FrontendConfEntity frontendConfEntity)
+        {
+            _mvnFilePath = mvnFilePath;
+            _frontendConfEntity = frontendConfEntity;
+            _fbank_beg_idx = 0;
+            _opts = KaldiNativeFbank.GetFbankOptions(
+                dither: _frontendConfEntity.dither,
+                snip_edges: true,
+                sample_rate: _frontendConfEntity.fs,
+                num_bins: _frontendConfEntity.n_mels
+                );
+            _cmvnEntity = LoadCmvn(mvnFilePath);
+        }
+
+        public float[] GetFbank(float[] samples)
+        {
+            float sample_rate = _frontendConfEntity.fs;
+            samples = samples.Select((float x) => x * 32768f).ToArray();
+            // method1
+            //FbankDatas fbankDatas = new FbankDatas();
+            //KaldiNativeFbank.GetFbanks(_knfOnlineFbank, framesNum,ref fbankDatas);
+            // method2
+            KnfOnlineFbank _knfOnlineFbank = KaldiNativeFbank.GetOnlineFbank(_opts);
+            KaldiNativeFbank.AcceptWaveform(_knfOnlineFbank, sample_rate, samples, samples.Length);
+            KaldiNativeFbank.InputFinished(_knfOnlineFbank);
+            int framesNum = KaldiNativeFbank.GetNumFramesReady(_knfOnlineFbank);
+            float[] fbanks = new float[framesNum * 80];
+            for (int i = 0; i < framesNum; i++)
+            {
+                FbankData fbankData = new FbankData();
+                KaldiNativeFbank.GetFbank(_knfOnlineFbank, i, ref fbankData);
+                float[] _fbankData = new float[fbankData.data_length];
+                Marshal.Copy(fbankData.data, _fbankData, 0, fbankData.data_length);
+                Array.Copy(_fbankData, 0, fbanks, i * 80, _fbankData.Length);
+                fbankData.data = IntPtr.Zero;
+                _fbankData = null;
+            }
+
+            samples = null;
+            GC.Collect();
+            return fbanks;
+        }
+
+
+        public float[] LfrCmvn(float[] fbanks)
+        {
+            float[] features = fbanks;
+            if (_frontendConfEntity.lfr_m != 1 || _frontendConfEntity.lfr_n != 1)
+            {
+                features = ApplyLfr(fbanks, _frontendConfEntity.lfr_m, _frontendConfEntity.lfr_n);
+            }
+            if (_cmvnEntity != null)
+            {
+                features = ApplyCmvn(features);
+            }
+            return features;
+        }
+
+        private float[] ApplyCmvn(float[] inputs)
+        {
+            var arr_neg_mean = _cmvnEntity.Means;
+            float[] neg_mean = arr_neg_mean.Select(x => (float)Convert.ToDouble(x)).ToArray();
+            var arr_inv_stddev = _cmvnEntity.Vars;
+            float[] inv_stddev = arr_inv_stddev.Select(x => (float)Convert.ToDouble(x)).ToArray();
+
+            int dim = neg_mean.Length;
+            int num_frames = inputs.Length / dim;
+
+            for (int i = 0; i < num_frames; i++)
+            {
+                for (int k = 0; k != dim; ++k)
+                {
+                    inputs[dim * i + k] = (inputs[dim * i + k] + neg_mean[k]) * inv_stddev[k];
+                }
+            }
+            return inputs;
+        }
+
+        public float[] ApplyLfr(float[] inputs, int lfr_m, int lfr_n)
+        {
+            int t = inputs.Length / 80;
+            int t_lfr = (int)Math.Floor((double)(t / lfr_n));
+            float[] input_0 = new float[80];
+            Array.Copy(inputs, 0, input_0, 0, 80);
+            int tile_x = (lfr_m - 1) / 2;
+            t = t + tile_x;
+            float[] inputs_temp = new float[t * 80];
+            for (int i = 0; i < tile_x; i++)
+            {
+                Array.Copy(input_0, 0, inputs_temp, tile_x * 80, 80);
+            }
+            Array.Copy(inputs, 0, inputs_temp, tile_x * 80, inputs.Length);
+            inputs = inputs_temp;
+
+            float[] LFR_outputs = new float[t_lfr * lfr_m * 80];
+            for (int i = 0; i < t_lfr; i++)
+            {
+                if (lfr_m <= t - i * lfr_n)
+                {
+                    Array.Copy(inputs, i * lfr_n * 80, LFR_outputs, i* lfr_m * 80, lfr_m * 80);
+                }
+                else
+                {
+                    // process last LFR frame
+                    int num_padding = lfr_m - (t - i * lfr_n);
+                    float[] frame = new float[lfr_m * 80];
+                    Array.Copy(inputs, i * lfr_n * 80, frame, 0, (t - i * lfr_n) * 80);
+
+                    for (int j = 0; j < num_padding; j++)
+                    {
+                        Array.Copy(inputs, (t - 1) * 80, frame, (lfr_m - num_padding + j) * 80, 80);
+                    }
+                    Array.Copy(frame, 0, LFR_outputs, i * lfr_m * 80, frame.Length);
+                }
+            }
+            return LFR_outputs;
+        }
+        
+        private CmvnEntity LoadCmvn(string mvnFilePath)
+        {
+            List<float> means_list = new List<float>();
+            List<float> vars_list = new List<float>();
+            FileStreamOptions options = new FileStreamOptions();
+            options.Access = FileAccess.Read;
+            options.Mode = FileMode.Open;
+            StreamReader srtReader = new StreamReader(mvnFilePath, options);
+            int i = 0;
+            while (!srtReader.EndOfStream)
+            {
+                string? strLine = srtReader.ReadLine();
+                if (!string.IsNullOrEmpty(strLine))
+                {
+                    if (strLine.StartsWith("<AddShift>")) 
+                    {
+                        i=1;
+                        continue;
+                    }
+                    if (strLine.StartsWith("<Rescale>"))
+                    {
+                        i = 2;
+                        continue;
+                    }
+                    if (strLine.StartsWith("<LearnRateCoef>") && i==1)
+                    {
+                        string[] add_shift_line = strLine.Substring(strLine.IndexOf("[") + 1, strLine.LastIndexOf("]") - strLine.IndexOf("[") - 1).Split(" ");
+                        means_list = add_shift_line.Where(x => !string.IsNullOrEmpty(x)).Select(x => float.Parse(x.Trim())).ToList();
+                        continue;
+                    }
+                    if (strLine.StartsWith("<LearnRateCoef>") && i==2)
+                    {
+                        string[] rescale_line = strLine.Substring(strLine.IndexOf("[") + 1, strLine.LastIndexOf("]") - strLine.IndexOf("[") - 1).Split(" ");
+                        vars_list = rescale_line.Where(x => !string.IsNullOrEmpty(x)).Select(x => float.Parse(x.Trim())).ToList();
+                        continue;
+                    }
+                }
+            }
+            CmvnEntity cmvnEntity = new CmvnEntity();
+            cmvnEntity.Means = means_list;
+            cmvnEntity.Vars = vars_list;
+            return cmvnEntity;
+        }
+
+    }
+}
diff --git a/funasr/runtime/csharp/AliFsmnVadSharp/WindowDetector.cs b/funasr/runtime/csharp/AliFsmnVadSharp/WindowDetector.cs
new file mode 100644
index 000000000..785af32b2
--- /dev/null
+++ b/funasr/runtime/csharp/AliFsmnVadSharp/WindowDetector.cs
@@ -0,0 +1,156 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+
+namespace AliFsmnVadSharp
+{
+    public enum FrameState
+    {
+        kFrameStateInvalid = -1,
+        kFrameStateSpeech = 1,
+        kFrameStateSil = 0
+    }
+
+    /// <summary>
+    /// final voice/unvoice state per frame
+    /// </summary>
+    public enum AudioChangeState
+    {
+        kChangeStateSpeech2Speech = 0,
+        kChangeStateSpeech2Sil = 1,
+        kChangeStateSil2Sil = 2,
+        kChangeStateSil2Speech = 3,
+        kChangeStateNoBegin = 4,
+        kChangeStateInvalid = 5
+    }
+
+
+    internal class WindowDetector
+    {
+        private int _window_size_ms = 0; //window_size_ms;
+        private int _sil_to_speech_time = 0; //sil_to_speech_time;
+        private int _speech_to_sil_time = 0; //speech_to_sil_time;
+        private int _frame_size_ms = 0; //frame_size_ms;
+
+        private int _win_size_frame = 0;
+        private int _win_sum = 0;
+        private int[] _win_state = new int[0];// * _win_size_frame;  // 初始化窗
+
+        private int _cur_win_pos = 0;
+        private int _pre_frame_state = (int)FrameState.kFrameStateSil;
+        private int _cur_frame_state = (int)FrameState.kFrameStateSil;
+        private int _sil_to_speech_frmcnt_thres = 0; //int(sil_to_speech_time / frame_size_ms);
+        private int _speech_to_sil_frmcnt_thres = 0; //int(speech_to_sil_time / frame_size_ms);
+
+        private int _voice_last_frame_count = 0;
+        private int _noise_last_frame_count = 0;
+        private int _hydre_frame_count = 0;
+
+        public WindowDetector()
+        {
+
+        }
+
+        public WindowDetector(int window_size_ms, int sil_to_speech_time, int speech_to_sil_time, int frame_size_ms)
+        {
+            _window_size_ms = window_size_ms;
+            _sil_to_speech_time = sil_to_speech_time;
+            _speech_to_sil_time = speech_to_sil_time;
+            _frame_size_ms = frame_size_ms;
+
+            _win_size_frame = (int)(window_size_ms / frame_size_ms);
+            _win_sum = 0;
+            _win_state = new int[_win_size_frame];//[0] * _win_size_frame;  // 初始化窗
+
+            _cur_win_pos = 0;
+            _pre_frame_state = (int)FrameState.kFrameStateSil;
+            _cur_frame_state = (int)FrameState.kFrameStateSil;
+            _sil_to_speech_frmcnt_thres = (int)(sil_to_speech_time / frame_size_ms);
+            _speech_to_sil_frmcnt_thres = (int)(speech_to_sil_time / frame_size_ms);
+
+            _voice_last_frame_count = 0;
+            _noise_last_frame_count = 0;
+            _hydre_frame_count = 0;
+        }
+
+        public void Reset()
+        {
+            _cur_win_pos = 0;
+            _win_sum = 0;
+            _win_state = new int[_win_size_frame];
+            _pre_frame_state = (int)FrameState.kFrameStateSil;
+            _cur_frame_state = (int)FrameState.kFrameStateSil;
+            _voice_last_frame_count = 0;
+            _noise_last_frame_count = 0;
+            _hydre_frame_count = 0;
+        }
+        
+
+        public int GetWinSize()
+        {
+            return _win_size_frame;
+        }
+
+        public AudioChangeState DetectOneFrame(FrameState frameState, int frame_count)
+        {
+
+
+            _cur_frame_state = (int)FrameState.kFrameStateSil;
+            if (frameState == FrameState.kFrameStateSpeech)
+            {
+                _cur_frame_state = 1;
+            }
+
+            else if (frameState == FrameState.kFrameStateSil)
+            {
+                _cur_frame_state = 0;
+            }
+
+            else
+            {
+                return AudioChangeState.kChangeStateInvalid;
+            }
+
+            _win_sum -= _win_state[_cur_win_pos];
+            _win_sum += _cur_frame_state;
+            _win_state[_cur_win_pos] = _cur_frame_state;
+            _cur_win_pos = (_cur_win_pos + 1) % _win_size_frame;
+
+            if (_pre_frame_state == (int)FrameState.kFrameStateSil && _win_sum >= _sil_to_speech_frmcnt_thres)
+            {
+                _pre_frame_state = (int)FrameState.kFrameStateSpeech;
+                return AudioChangeState.kChangeStateSil2Speech;
+            }
+
+
+            if (_pre_frame_state == (int)FrameState.kFrameStateSpeech && _win_sum <= _speech_to_sil_frmcnt_thres)
+            {
+                _pre_frame_state = (int)FrameState.kFrameStateSil;
+                return AudioChangeState.kChangeStateSpeech2Sil;
+            }
+
+
+            if (_pre_frame_state == (int)FrameState.kFrameStateSil)
+            {
+                return AudioChangeState.kChangeStateSil2Sil;
+            }
+
+            if (_pre_frame_state == (int)FrameState.kFrameStateSpeech)
+            {
+                return AudioChangeState.kChangeStateSpeech2Speech;
+            }
+
+            return AudioChangeState.kChangeStateInvalid;
+        }
+
+        private int FrameSizeMs()
+        {
+            return _frame_size_ms;
+        }
+
+
+
+    }
+}
diff --git a/funasr/runtime/csharp/README.md b/funasr/runtime/csharp/README.md
new file mode 100644
index 000000000..68175cd5a
--- /dev/null
+++ b/funasr/runtime/csharp/README.md
@@ -0,0 +1,59 @@
+# AliFsmnVadSharp
+##### 简介：
+项目中使用的VAD模型是阿里巴巴达摩院提供的FSMN-Monophone VAD模型。
+**项目基于Net 6.0，使用C#编写，调用Microsoft.ML.OnnxRuntime对onnx模型进行解码，支持跨平台编译。项目以库的形式进行调用，部署非常方便。**
+VAD整体流程的rtf在0.008左右。
+
+##### 用途：
+16k中文通用VAD模型：可用于检测长语音片段中有效语音的起止时间点.
+FSMN-Monophone VAD是达摩院语音团队提出的高效语音端点检测模型，用于检测输入音频中有效语音的起止时间点信息，并将检测出来的有效音频片段输入识别引擎进行识别，减少无效语音带来的识别错误。
+
+##### VAD常用参数调整说明（参考：vad.yaml文件）：
+max_end_silence_time：尾部连续检测到多长时间静音进行尾点判停，参数范围500ms～6000ms，默认值800ms(该值过低容易出现语音提前截断的情况)。
+speech_noise_thres：speech的得分减去noise的得分大于此值则判断为speech，参数范围：（-1,1）
+取值越趋于-1，噪音被误判定为语音的概率越大，FA越高
+取值越趋于+1，语音被误判定为噪音的概率越大，Pmiss越高
+通常情况下，该值会根据当前模型在长语音测试集上的效果取balance
+
+##### 模型获取
+
+##### 调用方式：
+###### 1.添加项目引用
+using AliFsmnVadSharp;
+
+###### 2.初始化模型和配置
+```csharp
+string applicationBase = AppDomain.CurrentDomain.BaseDirectory;
+string modelFilePath = applicationBase + "./speech_fsmn_vad_zh-cn-16k-common-pytorch/model.onnx";
+string configFilePath = applicationBase + "./speech_fsmn_vad_zh-cn-16k-common-pytorch/vad.yaml";
+string mvnFilePath = applicationBase + "./speech_fsmn_vad_zh-cn-16k-common-pytorch/vad.mvn";
+int batchSize = 2;//批量解码
+AliFsmnVad aliFsmnVad = new AliFsmnVad(modelFilePath, configFilePath, mvnFilePath, batchSize);
+```
+###### 3.调用
+方法一(适用于小文件)：
+```csharp
+SegmentEntity[] segments_duration = aliFsmnVad.GetSegments(samples);
+```
+方法二(适用于大文件)：
+```csharp
+SegmentEntity[] segments_duration = aliFsmnVad.GetSegmentsByStep(samples);
+```
+###### 4.输出结果：
+```
+load model and init config elapsed_milliseconds:463.5390625
+vad infer result:
+[[70,2340][2620,6200][6480,23670][23950,26250][26780,28990][29950,31430][31750,37600][38210,46900][47310,49630][49910,56460][56740,59540][59820,70450]]
+elapsed_milliseconds:662.796875
+total_duration:70470.625
+rtf:0.009405292985552491
+```
+输出的数据，例如：[70,2340]，是以毫秒为单位的segement的起止时间，可以以此为依据对音频进行分片。其中静音噪音部分已被去除。
+
+其他说明：
+测试用例：AliFsmnVadSharp.Examples。
+测试环境：windows11。
+测试用例中samples的计算,使用的是NAudio库。
+
+通过以下链接了解更多：
+https://www.modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary