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Real-time speech recognition and voice activity detection (VAD) using next-gen Kaldi with ncnn without Internet connection. Support iOS, Android, Linux, macOS, Windows, Raspberry Pi, VisionFive2, LicheePi4A etc.

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krmao/sherpa-ncnn

 
 

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Supported functions

Real-time Speech recognition Voice activity detection
✔️ ✔️

Supported platforms

Architecture Android iOS Windows macOS linux
x64 ✔️ ✔️ ✔️ ✔️
x86 ✔️ ✔️
arm64 ✔️ ✔️ ✔️ ✔️ ✔️
arm32 ✔️ ✔️
riscv64 ✔️

Supported programming languages

1. C++ 2. C 3. Python 4. JavaScript
✔️ ✔️ ✔️ ✔️
5. Go 6. C# 7. Kotlin 8. Swift
✔️ ✔️ ✔️ ✔️

It also supports WebAssembly.

Introduction

This repository supports running the following functions locally

  • Streaming speech-to-text (i.e., real-time speech recognition)
  • VAD (e.g., silero-vad)

on the following platforms and operating systems:

with the following APIs

  • C++, C, Python, Go, C#
  • Kotlin
  • JavaScript
  • Swift

We support all platforms that ncnn supports.

Everything can be compiled from source with static link. The generated executable depends only on system libraries.

HINT: It does not depend on PyTorch or any other inference frameworks other than ncnn.

Please see the documentation https://k2-fsa.github.io/sherpa/ncnn/index.html for installation and usages, e.g.,

  • How to build an Android app
  • How to download and use pre-trained models

We provide a few YouTube videos for demonstration about real-time speech recognition with sherpa-ncnn using a microphone:

Links for pre-built Android APKs

Description URL
Streaming speech recognition Address

Links for pre-trained models

https://github.com/k2-fsa/sherpa-ncnn/releases/tag/models

Useful links

How to reach us

Please see https://k2-fsa.github.io/sherpa/social-groups.html for 新一代 Kaldi 微信交流群 and QQ 交流群.

See also

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Real-time speech recognition and voice activity detection (VAD) using next-gen Kaldi with ncnn without Internet connection. Support iOS, Android, Linux, macOS, Windows, Raspberry Pi, VisionFive2, LicheePi4A etc.

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  • C++ 54.9%
  • CMake 9.5%
  • Shell 8.0%
  • Swift 5.9%
  • Python 5.2%
  • Kotlin 4.0%
  • Other 12.5%