doc/update README and CHANGELOG

CHANGELOG.md

@@ -1,18 +1,24 @@
 # Change log for esp-sr
 
+## 0.6.0
+update multinet_cn_1.4 and add CONTINUOUS RECOGNITION mode  
+improve hilexin wakeNet5X3 model(v5)    
+support IDFv4.0 build system  
+replace MAP algorithm with MASE(Mic Array Speech Enhancement) algorithm v1.0  
+
 ## 0.5.0
-add multinet1 English model v1.0
-update multinet1 Chinese model v2.0
-add Mic Array Processing(MAP) algorithm
-Fix the bug of parsing speech command
-fix the bug of decoder
+add multinet1 English model v1.0  
+update multinet1 Chinese model v2.0  
+add Mic Array Processing(MAP) algorithm  
+Fix the bug of parsing speech command  
+fix the bug of decoder  
 
 
 ## 0.3.0
-add wakenet6
-support cmake
-add free wake word: hi jeson
-update wakenet5X3 wake word model(v2)
+add wakenet6  
+support cmake  
+add free wake word: hi jeson  
+update wakenet5X3 wake word model(v2)  
 
 ## 0.2.0
 add acoustic algorithm, include AEC, AGC, VAD ,NS  

README.md

@@ -4,7 +4,7 @@ Espressif esp_sr provides basic algorithms for **Speech Recognition** applicatio
 
 * The wake word detection model [WakeNet](wake_word_engine/README.md)
 * The speech command recognition model [MultiNet](speech_command_recognition/README.md) 
-* Acoustic algorithm: AEC(Acoustic Echo Cancellation), VAD(Voice Activity Detection), AGC(Automatic Gain Control), NS(Noise Suppression)
+* Acoustic algorithm: MASE(Mic Array Speech Enhancement), AEC(Acoustic Echo Cancellation), VAD(Voice Activity Detection), AGC(Automatic Gain Control), NS(Noise Suppression)
 
 These algorithms are provided in the form of a component, so they can be integrated into your projects with minimum efforts.
 
@@ -19,3 +19,16 @@ Currently, Espressif has not only provided an official wake word "Hi, Lexin" to
 Espressif's speech command recognition model [MultiNet](speech_command_recognition/README.md) is specially designed to provide a flexible off-line speech command recognition model. With this model, you can easily add your own speech commands, eliminating the need to train model again.
 
 Currently, Espressif **MultiNet** supports up to 100 Chinese or English speech commands, such as “打开空调” (Turn on the air conditioner) and “打开卧室灯” (Turn on the bedroom light).
+
+
+## Acoustic algorithm
+
+Espressif acoustic algorithm module is specially designed to improve speech recognition performance in far-field or noisy environments. 
+
+Currently, MASE algorithm supports 2-mic linear array and 3-mic circular array.
+
+
+**In order to achieve optimal performance:**
+
+* Please refer to hardware design [ESP32_Korvo](https://github.com/espressif/esp-skainet/tree/master/docs/zh_CN/hw-reference/esp32/user-guide-esp32-korvo-v1.1.md) or [ESP32-LyraT-Mini](https://docs.espressif.com/projects/esp-adf/en/latest/get-started/get-started-esp32-lyrat-mini.html).
+* Please refer to software design [esp-skainet](https://github.com/espressif/esp-skainet).

README_cn.md

@@ -4,7 +4,7 @@ esp_sr 提供语音识别相关方向算法模型，目前主要包括三个模
 
 * 唤醒词识别模型 [WakeNet](wake_word_engine/README_cn.md)
 * 语音命令识别模型 [MultiNet](speech_command_recognition/README_cn.md) 
-* 声学算法：AEC(Acoustic Echo Cancellation), VAD(Voice Activity Detection), AGC(Automatic Gain Control), NS(Noise Suppression)
+* 声学算法：MASE(Mic Array Speech Enhancement), AEC(Acoustic Echo Cancellation), VAD(Voice Activity Detection), AGC(Automatic Gain Control), NS(Noise Suppression)
 
 这些算法以组件的形式提供，因此可以轻松地将它们集成到您的项目中。
 
@@ -20,3 +20,14 @@ esp_sr 提供语音识别相关方向算法模型，目前主要包括三个模
 
 目前模型支持类似“打开空调”，“打开卧室灯”等中文命令词识别和"Turn on/off the light" 等英文命令词识别，自定义语音命令词最大个数为 100。
 
+
+## 声学算法
+
+声学算法模块, 致力于提高复杂声学环境下的语音识别性能。MASE算法可有效改善远程或嘈杂环境下的语音识别性能。 
+
+目前MASE算法支持2-mic线性阵列和3-mic环形阵列。
+  
+**算法性能与硬件设计与软件配置息息相关，为达到最优性能:**  
+
+* 硬件设计建议参考 [ESP32_Korvo](https://github.com/espressif/esp-skainet/tree/master/docs/zh_CN/hw-reference/esp32/user-guide-esp32-korvo-v1.1.md) 或 [ESP32-LyraT-Mini](https://docs.espressif.com/projects/esp-adf/en/latest/get-started/get-started-esp32-lyrat-mini.html)。  
+* 软件设计建议参考 [esp-skainet](https://github.com/espressif/esp-skainet) 中相关示例。

acoustic_algorithm/include/esp_mase.h

@@ -67,7 +67,8 @@ mase_handle_t mase_create(int sample_rate, int frame_size, int array_type, float
  *
  * @return None
  *
- * @note Input is a multi-channel signal while the output is single-channel. For a 16-ms multi-channel input frame, the i-th point in the c-th channel should be indexed (i + c * 256).
+ * @note Input is a multi-channel signal while the output is single-channel. 
+ *       For a 16-ms multi-channel input frame, the i-th point in the c-th channel should be indexed (i + c * 256).
  *
  */
 void mase_process(mase_handle_t st, int16_t *in, int16_t *dsp_out);