websocket

funasr/runtime/python/websocket/ASR_client.py

@@ -1,5 +1,4 @@
-
-# import websocket #区别服务端这里是 websocket-client库
+# -*- encoding: utf-8 -*-
 import time
 import websockets
 import asyncio
@@ -50,18 +49,21 @@ async def record_microphone():
                     rate=RATE,
                     input=True,
                     frames_per_buffer=CHUNK)
-
+    is_speaking = True
     while True:
 
         data = stream.read(CHUNK)
+        data = data.decode('ISO-8859-1')
+        message = json.dumps({"chunk": args.chunk_size, "is_speaking": is_speaking, "audio": data})
         
-        voices.put(data)
+        voices.put(message)
         #print(voices.qsize())
 
         await asyncio.sleep(0.01)
 
 # 其他函数可以通过调用send(data)来发送数据，例如：
 async def record_from_scp():
+    import wave
     global voices
     if args.audio_in.endswith(".scp"):
         f_scp = open(args.audio_in)
@@ -71,15 +73,31 @@ async def record_from_scp():
     for wav in wavs:
         wav_splits = wav.strip().split()
         wav_path = wav_splits[1] if len(wav_splits) > 1 else wav_splits[0]
-        bytes = open(wav_path, "rb")
-        bytes = bytes.read()
-        
+        # bytes_f = open(wav_path, "rb")
+        # bytes_data = bytes_f.read()
+        with wave.open(wav_path, "rb") as wav_file:
+            # 获取音频参数
+            params = wav_file.getparams()
+            # 获取头信息的长度
+            # header_length = wav_file.getheaders()[0][1]
+            # 读取音频帧数据，跳过头信息
+            # wav_file.setpos(header_length)
+            frames = wav_file.readframes(wav_file.getnframes())
+
+        # 将音频帧数据转换为字节类型的数据
+        audio_bytes = bytes(frames)
         stride = int(args.chunk_size/1000*16000*2)
-        chunk_num = (len(bytes)-1)//stride + 1
+        chunk_num = (len(audio_bytes)-1)//stride + 1
+        print(stride)
+        is_speaking = True
         for i in range(chunk_num):
+            if i == chunk_num-1:
+                is_speaking = False
             beg = i*stride
-            data_chunk = bytes[beg:beg+stride]
-            voices.put(data_chunk)
+            data = audio_bytes[beg:beg+stride]
+            data = data.decode('ISO-8859-1')
+            message = json.dumps({"chunk": args.chunk_size, "is_speaking": is_speaking, "audio": data})
+            voices.put(message)
             # print("data_chunk: ", len(data_chunk))
             # print(voices.qsize())
         

funasr/runtime/python/websocket/ASR_server_streaming.py

@@ -0,0 +1,261 @@
+import asyncio
+import json
+import websockets
+import time
+from queue import Queue
+import threading
+import argparse
+
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+from modelscope.utils.logger import get_logger
+import logging
+import tracemalloc
+import numpy as np
+
+tracemalloc.start()
+
+logger = get_logger(log_level=logging.CRITICAL)
+logger.setLevel(logging.CRITICAL)
+
+
+websocket_users = set()  #维护客户端列表
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--host",
+                    type=str,
+                    default="0.0.0.0",
+                    required=False,
+                    help="host ip, localhost, 0.0.0.0")
+parser.add_argument("--port",
+                    type=int,
+                    default=10095,
+                    required=False,
+                    help="grpc server port")
+parser.add_argument("--asr_model",
+                    type=str,
+                    default="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch",
+                    help="model from modelscope")
+parser.add_argument("--vad_model",
+                    type=str,
+                    default="damo/speech_fsmn_vad_zh-cn-16k-common-pytorch",
+                    help="model from modelscope")
+
+parser.add_argument("--punc_model",
+                    type=str,
+                    default="damo/punc_ct-transformer_zh-cn-common-vad_realtime-vocab272727",
+                    help="model from modelscope")
+parser.add_argument("--ngpu",
+                    type=int,
+                    default=1,
+                    help="0 for cpu, 1 for gpu")
+
+args = parser.parse_args()
+
+print("model loading")
+
+def load_bytes(input):
+    middle_data = np.frombuffer(input, dtype=np.int16)
+    middle_data = np.asarray(middle_data)
+    if middle_data.dtype.kind not in 'iu':
+        raise TypeError("'middle_data' must be an array of integers")
+    dtype = np.dtype('float32')
+    if dtype.kind != 'f':
+        raise TypeError("'dtype' must be a floating point type")
+
+    i = np.iinfo(middle_data.dtype)
+    abs_max = 2 ** (i.bits - 1)
+    offset = i.min + abs_max
+    array = np.frombuffer((middle_data.astype(dtype) - offset) / abs_max, dtype=np.float32)
+    return array
+
+# vad
+inference_pipeline_vad = pipeline(
+    task=Tasks.voice_activity_detection,
+    model=args.vad_model,
+    model_revision=None,
+    output_dir=None,
+    batch_size=1,
+    mode='online',
+    ngpu=args.ngpu,
+)
+# param_dict_vad = {'in_cache': dict(), "is_final": False}
+  
+# # asr
+# param_dict_asr = {}
+# # param_dict["hotword"] = "小五 小五月"  # 设置热词，用空格隔开
+# inference_pipeline_asr = pipeline(
+#     task=Tasks.auto_speech_recognition,
+#     model=args.asr_model,
+#     param_dict=param_dict_asr,
+#     ngpu=args.ngpu,
+# )
+# if args.punc_model != "":
+#     # param_dict_punc = {'cache': list()}
+#     inference_pipeline_punc = pipeline(
+#         task=Tasks.punctuation,
+#         model=args.punc_model,
+#         model_revision=None,
+#         ngpu=args.ngpu,
+#     )
+# else:
+#     inference_pipeline_punc = None
+
+
+inference_pipeline_asr_online = pipeline(
+    task=Tasks.auto_speech_recognition,
+    model='damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online',
+    model_revision=None)
+
+
+print("model loaded")
+
+
+
+async def ws_serve(websocket, path):
+    #speek = Queue()
+    frames = []  # 存储所有的帧数据
+    frames_online = []  # 存储所有的帧数据
+    buffer = []  # 存储缓存中的帧数据（最多两个片段）
+    RECORD_NUM = 0
+    global websocket_users
+    speech_start, speech_end = False, False
+    # 调用asr函数
+    websocket.param_dict_vad = {'in_cache': dict(), "is_final": False}
+    websocket.param_dict_punc = {'cache': list()}
+    websocket.speek = Queue()  #websocket 添加进队列对象 让asr读取语音数据包
+    websocket.send_msg = Queue()   #websocket 添加个队列对象  让ws发送消息到客户端
+    websocket_users.add(websocket)
+    # ss = threading.Thread(target=asr, args=(websocket,))
+    # ss.start()
+    
+    websocket.param_dict_asr_online = {"cache": dict(), "is_final": False}
+    websocket.speek_online = Queue()  # websocket 添加进队列对象 让asr读取语音数据包
+    ss_online = threading.Thread(target=asr_online, args=(websocket,))
+    ss_online.start()
+    
+    try:
+        async for data in websocket:
+            #voices.put(message)
+            #print("put")
+            #await websocket.send("123")
+            
+            data = json.loads(data)
+            # message = data["data"]
+            message = bytes(data['audio'], 'ISO-8859-1')
+            chunk = data["chunk"]
+            chunk_num = 600//chunk
+            is_speaking = data["is_speaking"]
+            websocket.param_dict_vad["is_final"] = not is_speaking
+            buffer.append(message)
+            if len(buffer) > 2:
+                buffer.pop(0)  # 如果缓存超过两个片段，则删除最早的一个
+              
+            if speech_start:
+                # frames.append(message)
+                frames_online.append(message)
+                # RECORD_NUM += 1
+                if len(frames_online) % chunk_num == 0:
+                    audio_in = b"".join(frames_online)
+                    websocket.speek_online.put(audio_in)
+                    frames_online = []
+
+            speech_start_i, speech_end_i = vad(message, websocket)
+            #print(speech_start_i, speech_end_i)
+            if speech_start_i:
+                # RECORD_NUM += 1
+                speech_start = speech_start_i
+                # frames = []
+                # frames.extend(buffer)  # 把之前2个语音数据快加入
+                frames_online = []
+                # frames_online.append(message)
+                frames_online.extend(buffer)
+                # RECORD_NUM += 1
+                websocket.param_dict_asr_online["is_final"] = False
+            if speech_end_i:
+                speech_start = False
+                # audio_in = b"".join(frames)
+                # websocket.speek.put(audio_in)
+                # frames = []  # 清空所有的帧数据
+                frames_online = []
+                websocket.param_dict_asr_online["is_final"] = True
+                # buffer = []  # 清空缓存中的帧数据（最多两个片段）
+                # RECORD_NUM = 0
+            if not websocket.send_msg.empty():
+                await websocket.send(websocket.send_msg.get())
+                websocket.send_msg.task_done()
+
+     
+    except websockets.ConnectionClosed:
+        print("ConnectionClosed...", websocket_users)    # 链接断开
+        websocket_users.remove(websocket)
+    except websockets.InvalidState:
+        print("InvalidState...")    # 无效状态
+    except Exception as e:
+        print("Exception:", e)
+ 
+
+# def asr(websocket):  # ASR推理
+#         global inference_pipeline_asr
+#         # global param_dict_punc
+#         global websocket_users
+#         while websocket in  websocket_users:
+#             if not websocket.speek.empty():
+#                 audio_in = websocket.speek.get()
+#                 websocket.speek.task_done()
+#                 if len(audio_in) > 0:
+#                     rec_result = inference_pipeline_asr(audio_in=audio_in)
+#                     if inference_pipeline_punc is not None and 'text' in rec_result:
+#                         rec_result = inference_pipeline_punc(text_in=rec_result['text'], param_dict=websocket.param_dict_punc)
+#                     # print(rec_result)
+#                     if "text" in rec_result:
+#                         message = json.dumps({"mode": "offline", "text": rec_result["text"]})
+#                         websocket.send_msg.put(message)  # 存入发送队列  直接调用send发送不了
+#
+#             time.sleep(0.1)
+
+
+def asr_online(websocket):  # ASR推理
+    global inference_pipeline_asr_online
+    # global param_dict_punc
+    global websocket_users
+    while websocket in websocket_users:
+        if not websocket.speek_online.empty():
+            audio_in = websocket.speek_online.get()
+            websocket.speek_online.task_done()
+            if len(audio_in) > 0:
+                # print(len(audio_in))
+                audio_in = load_bytes(audio_in)
+                # print(audio_in.shape)
+                rec_result = inference_pipeline_asr_online(audio_in=audio_in, param_dict=websocket.param_dict_asr_online)
+
+                # print(rec_result)
+                if "text" in rec_result:
+                    if rec_result["text"] != "sil" and rec_result["text"] != "waiting_for_more_voice":
+                        message = json.dumps({"mode": "online", "text": rec_result["text"]})
+                        websocket.send_msg.put(message)  # 存入发送队列  直接调用send发送不了
+        
+        time.sleep(0.1)
+
+def vad(data, websocket):  # VAD推理
+    global inference_pipeline_vad, param_dict_vad
+    #print(type(data))
+    # print(param_dict_vad)
+    segments_result = inference_pipeline_vad(audio_in=data, param_dict=websocket.param_dict_vad)
+    # print(segments_result)
+    # print(param_dict_vad)
+    speech_start = False
+    speech_end = False
+    
+    if len(segments_result) == 0 or len(segments_result["text"]) > 1:
+        return speech_start, speech_end
+    if segments_result["text"][0][0] != -1:
+        speech_start = True
+    if segments_result["text"][0][1] != -1:
+        speech_end = True
+    return speech_start, speech_end
+
+ 
+start_server = websockets.serve(ws_serve, args.host, args.port, subprotocols=["binary"], ping_interval=None)
+asyncio.get_event_loop().run_until_complete(start_server)
+asyncio.get_event_loop().run_forever()

funasr/runtime/python/websocket/ASR_server_streaming_asr.py

@@ -0,0 +1,149 @@
+import asyncio
+import json
+import websockets
+import time
+from queue import Queue
+import threading
+import argparse
+
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+from modelscope.utils.logger import get_logger
+import logging
+import tracemalloc
+import numpy as np
+
+tracemalloc.start()
+
+logger = get_logger(log_level=logging.CRITICAL)
+logger.setLevel(logging.CRITICAL)
+
+
+websocket_users = set()  #维护客户端列表
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--host",
+                    type=str,
+                    default="0.0.0.0",
+                    required=False,
+                    help="host ip, localhost, 0.0.0.0")
+parser.add_argument("--port",
+                    type=int,
+                    default=10095,
+                    required=False,
+                    help="grpc server port")
+parser.add_argument("--asr_model",
+                    type=str,
+                    default="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch",
+                    help="model from modelscope")
+parser.add_argument("--vad_model",
+                    type=str,
+                    default="damo/speech_fsmn_vad_zh-cn-16k-common-pytorch",
+                    help="model from modelscope")
+
+parser.add_argument("--punc_model",
+                    type=str,
+                    default="damo/punc_ct-transformer_zh-cn-common-vad_realtime-vocab272727",
+                    help="model from modelscope")
+parser.add_argument("--ngpu",
+                    type=int,
+                    default=1,
+                    help="0 for cpu, 1 for gpu")
+
+args = parser.parse_args()
+
+print("model loading")
+
+def load_bytes(input):
+    middle_data = np.frombuffer(input, dtype=np.int16)
+    middle_data = np.asarray(middle_data)
+    if middle_data.dtype.kind not in 'iu':
+        raise TypeError("'middle_data' must be an array of integers")
+    dtype = np.dtype('float32')
+    if dtype.kind != 'f':
+        raise TypeError("'dtype' must be a floating point type")
+
+    i = np.iinfo(middle_data.dtype)
+    abs_max = 2 ** (i.bits - 1)
+    offset = i.min + abs_max
+    array = np.frombuffer((middle_data.astype(dtype) - offset) / abs_max, dtype=np.float32)
+    return array
+
+inference_pipeline_asr_online = pipeline(
+    task=Tasks.auto_speech_recognition,
+    # model='damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online',
+    model='damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online',
+    model_revision=None)
+
+
+print("model loaded")
+
+
+
+async def ws_serve(websocket, path):
+    frames_online = []
+    global websocket_users
+    websocket.send_msg = Queue()
+    websocket_users.add(websocket)
+    websocket.param_dict_asr_online = {"cache": dict()}
+    websocket.speek_online = Queue()
+    ss_online = threading.Thread(target=asr_online, args=(websocket,))
+    ss_online.start()
+    try:
+        async for message in websocket:
+            message = json.loads(message)
+            audio = bytes(message['audio'], 'ISO-8859-1')
+            chunk = message["chunk"]
+            chunk_num = 500//chunk
+            is_speaking = message["is_speaking"]
+            websocket.param_dict_asr_online["is_final"] = not is_speaking
+            frames_online.append(audio)
+
+            if len(frames_online) % chunk_num == 0 or not is_speaking:
+                audio_in = b"".join(frames_online)
+                websocket.speek_online.put(audio_in)
+                frames_online = []
+
+            if not websocket.send_msg.empty():
+                await websocket.send(websocket.send_msg.get())
+                websocket.send_msg.task_done()
+
+     
+    except websockets.ConnectionClosed:
+        print("ConnectionClosed...", websocket_users)    # 链接断开
+        websocket_users.remove(websocket)
+    except websockets.InvalidState:
+        print("InvalidState...")    # 无效状态
+    except Exception as e:
+        print("Exception:", e)
+ 
+
+
+def asr_online(websocket):  # ASR推理
+    global inference_pipeline_asr_online
+    global websocket_users
+    while websocket in websocket_users:
+        if not websocket.speek_online.empty():
+            audio_in = websocket.speek_online.get()
+            websocket.speek_online.task_done()
+            if len(audio_in) > 0:
+                # print(len(audio_in))
+                audio_in = load_bytes(audio_in)
+                # print(audio_in.shape)
+                print(websocket.param_dict_asr_online["is_final"])
+                rec_result = inference_pipeline_asr_online(audio_in=audio_in, param_dict=websocket.param_dict_asr_online)
+                if websocket.param_dict_asr_online["is_final"]:
+                    websocket.param_dict_asr_online["cache"] = dict()
+
+                print(rec_result)
+                if "text" in rec_result:
+                    if rec_result["text"] != "sil" and rec_result["text"] != "waiting_for_more_voice":
+                        message = json.dumps({"mode": "online", "text": rec_result["text"]})
+                        websocket.send_msg.put(message)  # 存入发送队列  直接调用send发送不了
+        
+        time.sleep(0.005)
+
+ 
+start_server = websockets.serve(ws_serve, args.host, args.port, subprotocols=["binary"], ping_interval=None)
+asyncio.get_event_loop().run_until_complete(start_server)
+asyncio.get_event_loop().run_forever()