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Дрво: 2e89994fc6
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sherpa-ncnn
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Fangjun Kuang 2e89994fc6 Fix building. (#325) пре 1 година
.github 2e89994fc6 Fix building. (#325) пре 1 година
android ca9c19facd Add Android WearOS demo (#319) пре 1 година
c-api-examples 401de81194 Add hotwords support to Swift/Go/Python/C#/Kotlin APIs (#260) пре 1 година
cmake 884ce6d9eb Use tencent/ncnn master. (#320) пре 1 година
dotnet-examples 77c34f3cff Add microphone example for .Net (#248) пре 2 година
ffmpeg-examples 0ba47330ce FFmpeg: Feed PCM to K2 direclty, without any buffer. (#183) пре 2 година
go-api-examples 343eab32ab Update sherpa-ncnn-go version (#245) пре 2 година
ios-swift b4260f7acf Refactor code (#163) пре 2 година
ios-swiftui f12aac47c3 Add SwiftUI demo project (#175) пре 2 година
mfc-examples 98ba3218db Fix MFC examples (#268) пре 1 година
nodejs-examples 41ebcfb11b Add WebAssembly + NodeJS example. (#311) пре 1 година
python-api-examples 87899c26fe Add Python ASR example with alsa (#324) пре 1 година
scripts 2e89994fc6 Fix building. (#325) пре 1 година
sherpa-ncnn 2e89994fc6 Fix building. (#325) пре 1 година
swift-api-examples 401de81194 Add hotwords support to Swift/Go/Python/C#/Kotlin APIs (#260) пре 1 година
toolchains f9a850c725 Support RISC-V (#213) пре 2 година
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build-swift-macos.sh da14875cbb Refactor decoding (#132) пре 2 година
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README.md

Introduction

You can use sherpa-ncnn for real-time speech recognition (i.e., speech-to-text) on

  • Linux
  • macOS
  • Windows
  • Embedded Linux (32-bit arm and 64-bit aarch64)
  • Android
  • etc ...

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:

See also https://github.com/k2-fsa/sherpa