• 描述 目前大多数语音识别系统都将语音数据发送到云端处理，不可避免地会带来网络延时、数据安全等问题，作为对比，设备端本地的语音识别具有高可靠性、高安全性和迅速响应等特点。另一方面，AliOS Things通常运行在CPU时钟频率较低且存储资源非常有限的MCU上，因此对算法本身的复杂度、资源占用和准确性提出了很高的要求。

• Description At present, most voice recognition systems send voice data to cloud for processing, which inevitably brings problems such as network delay and data security. In contrast, local voice recognition on the device side has advantages such as high reliability, high security and rapid response. On the other hand, AliOS Things usually runs on an MCU with a low CPU clock frequency and very limited storage resources, so it puts high demands on the complexity, resource consumption and accuracy of the algorithm itself.

• 目标 基于AliOS Things开发离线语音能力，包括但不限于语音识别、声纹识别、语音合成等。

• Goal Develop offline voice capabilities based on AliOS Things, including but not limited to speech recognition, voiceprint recognition, speech synthesis, and more.

• 参考 基于AliOS Things的声纹识别算法 基于AliOS Things，在设备端MCU上实现一种声纹识别算法，可以根据1段预先录音的PCM格式的录音数据，判断正在录音的声音是否是同一个人的声音。预录的PCM格式的录音时长在10秒左右，要求录音结束后5秒左右可以判断出结果，判断的准确率在80%以上。算法不限，即使用可传统的语音识别，亦可集成某种轻量级AI框架，但要求在设备端MCU上运行，不能将语音数据上传到云端进行判断。

• Reference Voiceprint recognition algorithm based on AliOS Things Based on AliOS Things, a voiceprint recognition algorithm is implemented on MCU side, and it is possible to determine whether the sound being recorded is the same person's voice based on the recorded data in PCM format of the pre-recorded voice. The recording time of the pre-recorded PCM format is about 10 seconds, and the result can be judged about 5 seconds after the end of the recording, and the accuracy of the judgment is over 80%. The algorithm is not limited, that is, the traditional speech recognition can be used, or a certain lightweight AI framework can be integrated. But it is required to run on MCU side, with the voice data not being uploaded to cloud.

该提问来源于开源项目：alibaba/AliOS-Things