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Project description
Supported functions
Speech recognition | Speech synthesis | Speaker verification | Speaker identification |
---|---|---|---|
✔️ | ✔️ | ✔️ | ✔️ |
Spoken Language identification | Audio tagging | Voice activity detection |
---|---|---|
✔️ | ✔️ | ✔️ |
Keyword spotting | Add punctuation |
---|---|
✔️ | ✔️ |
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. Java | 6. C# | 7. Kotlin | 8. Swift |
---|---|---|---|
✔️ | ✔️ | ✔️ | ✔️ |
9. Go | 10. Dart | 11. Rust | 12. Pascal |
---|---|---|---|
✔️ | ✔️ | ✔️ | ✔️ |
For Rust support, please see sherpa-rs
It also supports WebAssembly.
Introduction
This repository supports running the following functions locally
- Speech-to-text (i.e., ASR); both streaming and non-streaming are supported
- Text-to-speech (i.e., TTS)
- Speaker identification
- Speaker verification
- Spoken language identification
- Audio tagging
- VAD (e.g., silero-vad)
- Keyword spotting
on the following platforms and operating systems:
- x86,
x86_64
, 32-bit ARM, 64-bit ARM (arm64, aarch64), RISC-V (riscv64) - Linux, macOS, Windows, openKylin
- Android, WearOS
- iOS
- NodeJS
- WebAssembly
- Raspberry Pi
- RV1126
- LicheePi4A
- VisionFive 2
- 旭日X3派
- 爱芯派
- etc
with the following APIs
- C++, C, Python, Go,
C#
- Java, Kotlin, JavaScript
- Swift, Rust
- Dart, Object Pascal
Links for Huggingface Spaces
You can visit the following Huggingface spaces to try sherpa-onnx
without
installing anything. All you need is a browser.
Description | URL |
---|---|
Speech recognition | Click me |
Speech recognition with Whisper | Click me |
Speech synthesis | Click me |
Generate subtitles | Click me |
Audio tagging | Click me |
Spoken language identification with Whisper | Click me |
We also have spaces built using WebAssembly. They are listed below:
Description | Huggingface space | ModelScope space |
---|---|---|
Voice activity detection with silero-vad | Click me | 地址 |
Real-time speech recognition (Chinese + English) with Zipformer | Click me | 地址 |
Real-time speech recognition (Chinese + English) with Paraformer | Click me | 地址 |
Real-time speech recognition (Chinese + English + Cantonese) with Paraformer-large | Click me | 地址 |
Real-time speech recognition (English) | Click me | 地址 |
VAD + speech recognition (Chinese + English + Korean + Japanese + Cantonese) with SenseVoice | Click me | 地址 |
VAD + speech recognition (English) with Whisper tiny.en | Click me | 地址 |
VAD + speech recognition (English) with Zipformer trained with GigaSpeech | Click me | 地址 |
VAD + speech recognition (Chinese) with Zipformer trained with WenetSpeech | Click me | 地址 |
VAD + speech recognition (Japanese) with Zipformer trained with ReazonSpeech | Click me | 地址 |
VAD + speech recognition (Thai) with Zipformer trained with GigaSpeech2 | Click me | 地址 |
VAD + speech recognition (Chinese 多种方言) with a TeleSpeech-ASR CTC model | Click me | 地址 |
VAD + speech recognition (English + Chinese, 及多种中文方言) with Paraformer-large | Click me | 地址 |
VAD + speech recognition (English + Chinese, 及多种中文方言) with Paraformer-small | Click me | 地址 |
Speech synthesis (English) | Click me | 地址 |
Speech synthesis (German) | Click me | 地址 |
Links for pre-built Android APKs
Description | URL | 中国用户 |
---|---|---|
Streaming speech recognition | Address | 点此 |
Text-to-speech | Address | 点此 |
Voice activity detection (VAD) | Address | 点此 |
VAD + non-streaming speech recognition | Address | 点此 |
Two-pass speech recognition | Address | 点此 |
Audio tagging | Address | 点此 |
Audio tagging (WearOS) | Address | 点此 |
Speaker identification | Address | 点此 |
Spoken language identification | Address | 点此 |
Keyword spotting | Address | 点此 |
Links for pre-built Flutter APPs
Real-time speech recognition
Description | URL | 中国用户 |
---|---|---|
Streaming speech recognition | Address | 点此 |
Text-to-speech
Description | URL | 中国用户 |
---|---|---|
Android (arm64-v8a, armeabi-v7a, x86_64) | Address | 点此 |
Linux (x64) | Address | 点此 |
macOS (x64) | Address | 点此 |
macOS (arm64) | Address | 点此 |
Windows (x64) | Address | 点此 |
Note: You need to build from source for iOS.
Links for pre-built Lazarus APPs
Generating subtitles
Description | URL | 中国用户 |
---|---|---|
Generate subtitles (生成字幕) | Address | 点此 |
Links for pre-trained models
Description | URL |
---|---|
Speech recognition (speech to text, ASR) | Address |
Text-to-speech (TTS) | Address |
VAD | Address |
Keyword spotting | Address |
Audio tagging | Address |
Speaker identification (Speaker ID) | Address |
Spoken language identification (Language ID) | See multi-lingual Whisper ASR models from Speech recognition |
Punctuation | Address |
Useful links
- Documentation: https://k2-fsa.github.io/sherpa/onnx/
- Bilibili 演示视频: https://search.bilibili.com/all?keyword=%E6%96%B0%E4%B8%80%E4%BB%A3Kaldi
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.
Projects using sherpa-onnx
voiceapi
Streaming ASR and TTS based on FastAPI
It shows how to use the ASR and TTS Python APIs with FastAPI.
TMSpeech
Uses streaming ASR in C# with graphical user interface.
Project details
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MD5 | e1432d117a788866e6c58ef3f16978e2 |
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BLAKE2b-256 | 2af94cfbc55938ddaa502845a3e7a304df21f614707756380d432549f788a7f4 |
Hashes for sherpa_onnx-1.10.27-cp38-cp38-macosx_11_0_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | 8b664e5447799c62c0d575ca0fada66397cf01f723168f905b0e5f09b3a5e5ba |
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MD5 | e376a1f54fb550c3c4ba2faeb52f5e74 |
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BLAKE2b-256 | e0d13e4374850eb397038d3314343b2d33fef5ece7ec7a65315605206ab39fd8 |
Hashes for sherpa_onnx-1.10.27-cp38-cp38-macosx_11_0_universal2.whl
Algorithm | Hash digest | |
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SHA256 | 7a981daccc4ab1a945b45573861e027c5d2304656afef721be07e2218de4a2cb |
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MD5 | fc77ecd99dc5c438021a07b4ee0e65b7 |
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BLAKE2b-256 | 5d5c7d88044a7b5b15ad9afd1e2594d04c656debfa4c14d5e0b21e138bbd632f |
Hashes for sherpa_onnx-1.10.27-cp38-cp38-macosx_11_0_arm64.whl
Algorithm | Hash digest | |
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SHA256 | db26ec90ba7f3686a45fbee77e3f955e54b483da5079555dc3f507117a132ea8 |
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MD5 | 13b5292796485dc60b3c2329555e9214 |
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BLAKE2b-256 | bf7102ff84b90e9c63709cde1794b565406b4c47965f418517cdf6783a86de4d |
Hashes for sherpa_onnx-1.10.27-cp38-cp38-linux_armv7l.whl
Algorithm | Hash digest | |
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SHA256 | a602f8979344be37aef7ebadc815f72e646b9b91451b0f850a2e515589b397e5 |
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MD5 | d9a768a80682d91d306e41354c004ee0 |
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BLAKE2b-256 | 47236d7e0fdd1dce1d185b53648727ebfac280275889b013def1e5c947e81317 |
Hashes for sherpa_onnx-1.10.27-cp37-cp37m-win_amd64.whl
Algorithm | Hash digest | |
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SHA256 | 41d901015de7b234f7c791c8e3d120d9d54a0e7db29675dc7f6637c1f0ecb55e |
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MD5 | 9908273ae60cc31fc4fd0fd69562f723 |
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BLAKE2b-256 | ece9ab581c649587c04299e7472b25f19941dbf5cde1ca7e5bd2d32a17f194d2 |
Hashes for sherpa_onnx-1.10.27-cp37-cp37m-win32.whl
Algorithm | Hash digest | |
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SHA256 | f8941b88755e0ac40a3e146bf38fa98ba4bf4a4bac0ec7d330a344fac7f7b379 |
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MD5 | 15196447fa6ff722b2a2dde46b115836 |
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BLAKE2b-256 | 8af84d74eef282c17d2cd157914b8587754a0d49df2e92777b4188a1a8c86825 |
Hashes for sherpa_onnx-1.10.27-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9e5c64c7fa386cf9de731e97ef146be8bef6a223c977d0f5f445e98500d93bdf |
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MD5 | bf2e634da653ae65e81febc4c0b92b7a |
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BLAKE2b-256 | fbfea29cab6eebff45aa69f406986c07017550b6b4543a2a1eb667a1ab156620 |
Hashes for sherpa_onnx-1.10.27-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0c64eb35e8ebb5b1c7fd5620e203165c8d54858ef7c26ae595e23642f97c6d71 |
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MD5 | a121180eaced1dc58fdd8903ead80985 |
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BLAKE2b-256 | 75ff4aad05be3e8a0ed263bfdb8ac373b4bc9020b5ec7c9bb9d6f2ed49b7433d |
Hashes for sherpa_onnx-1.10.27-cp37-cp37m-macosx_11_0_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d922a46b4dfaf58b4e43bb4417947b3a2b5618290fc13148ba8437ec821698c1 |
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MD5 | 39fd5262017e2d3144777fd04de1f835 |
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BLAKE2b-256 | 5b591334dd84a0c8fe855fde03559c1227b45a3224eda67e592ba9db94128c77 |
Hashes for sherpa_onnx-1.10.27-cp37-cp37m-linux_armv7l.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b7a7b00a11fbc36072d85f12f84087989ea30a8cf816a3323bc6ae15ad70c752 |
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MD5 | d67b5d114739b0da8ce74ec66ab9d343 |
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BLAKE2b-256 | e28eb0c23b6d05d62cb58a8575c66de72aa402ac60da98b27b4a1a4d746ec8cb |