enginex-mr_series-sherpa-onnx/harmony-os/SherpaOnnxHar/sherpa_onnx/README.md

# Introduction

[sherpa-onnx](https://github.com/k2-fsa/sherpa-onnx) is one of the deployment
frameworks of [Next-gen Kaldi](https://github.com/k2-fsa).

It supports speech-to-text, text-to-speech, speaker diarization, and VAD using
onnxruntime without Internet connection.

It also supports embedded systems, Android, iOS, HarmonyOS,
Raspberry Pi, RISC-V, x86_64 servers, websocket server/client,
C/C++, Python, Kotlin, C#, Go, NodeJS, Java, Swift, Dart, JavaScript,
Flutter, Object Pascal, Lazarus, Rust, etc.


# Installation

To use `sherpa-onnx` in your project, please either use

```
ohpm install sherpa_onnx
```
or update your `oh-package.json5` to include the following:

```
  "dependencies": {
    "sherpa_onnx": "1.10.36",
  },
```

Note that we recommend always using the latest version.

# Examples

| Demo | URL | Description|
|------|-----|------------|
|SherpaOnnxStreamingAsr|[Address](https://github.com/k2-fsa/sherpa-onnx/tree/master/harmony-os/SherpaOnnxStreamingAsr)|On-device real-time/streaming speech recognition with Next-gen Kaldi|
|SherpaOnnxVadAsr|[Address](https://github.com/k2-fsa/sherpa-onnx/tree/master/harmony-os/SherpaOnnxVadAsr)|It shows how to use VAD with a non-streaming ASR model for on-device speech recognition without accessing the network |
|SherpaOnnxTts|[Address](https://github.com/k2-fsa/sherpa-onnx/tree/master/harmony-os/SherpaOnnxTts)|It shows how to use Next-gen Kaldi for on-device text-to-speech (TTS, i.e., speech synthesis)|
|SherpaOnnxSpeakerDiarization|[Address](https://github.com/k2-fsa/sherpa-onnx/tree/master/harmony-os/SherpaOnnxSpeakerDiarization)|On-device speaker diarization with Next-gen Kaldi|
|SherpaOnnxSpeakerIdentification|[Address](https://github.com/k2-fsa/sherpa-onnx/tree/master/harmony-os/SherpaOnnxSpeakerIdentification)|On-device speaker identification with Next-gen Kaldi|

# Documentation

If you have any issues, please either look at our doc at
<https://k2-fsa.github.io/sherpa/onnx/> or create an issue at
<https://github.com/k2-fsa/sherpa-onnx/issues>