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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 https://github.com/thewh1teagle/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
- etc
with the following APIs
- C++, C, Python, Go,
C#
- Java, Kotlin, JavaScript
- Swift, Rust
- Dart, Object Pascal
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.
Project details
Release history Release notifications | RSS feed
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SHA256 | 6edae466c820fb943abeccf9bde55631c9054b757a444d2118197f920776d9fd |
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MD5 | 40833e5746e78cdf8e4f419673770b00 |
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BLAKE2b-256 | 4b9236383da61fd412fc8ce3ebb2c09232c792863710acaefe12867902f52b8e |
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Hashes for sherpa_onnx-1.10.22-cp38-cp38-linux_armv7l.whl
Algorithm | Hash digest | |
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SHA256 | f5e021425f8dc0749a600e25f824857e33161abd189f864068381d72da21f392 |
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MD5 | c3ecbd75780d183948e18c5bedd6c160 |
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BLAKE2b-256 | 7553238145a194348748e84b7105177044a244e07785dfc6fa36d4d5772f7289 |
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Hashes for sherpa_onnx-1.10.22-cp37-cp37m-win_amd64.whl
Algorithm | Hash digest | |
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SHA256 | ea1ca2a19d2c4713080e3319fa56d66adc4e3f3b36238d2bf891731799ae5acb |
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MD5 | 220ef7c93a5288ca0a8afe5283cf0305 |
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BLAKE2b-256 | 4c739a4c6be0580a1cb333bf0d0b3f77076a9eee76112c38e582bc263a519dd7 |
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Hashes for sherpa_onnx-1.10.22-cp37-cp37m-win32.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | c24baf341dd318f160504df1df5bf1310e744c0ee9680e1106a0df5be1480579 |
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MD5 | 1f8e1dbe2c68ab23fcd94baef87added |
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BLAKE2b-256 | bc23c8511e1af8466d1220dcaeb23665cb64b828bde23559a68c26e01ff94e34 |
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Hashes for sherpa_onnx-1.10.22-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | d24a9997d97c86da0fa7716c9fa0590a0748ce211cd2db328bdf008b77f3127d |
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MD5 | ae22a634f9c0502e62e173621d0ebc29 |
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BLAKE2b-256 | 78915444574896d260ad28788f64fb2501ea660e4bde8666d1bfc87d973d0db3 |
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Hashes for sherpa_onnx-1.10.22-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d905930c595e7f2438a458928decdbee80f500dcbd01f4e513cbeac51bb38d9b |
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MD5 | ec93914e68a435a9a16245088326fba5 |
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BLAKE2b-256 | 0cee4096a54dc6c8303b1c39a63632f09e468b8c51b6f18709ee7c28ce48a83c |
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Hashes for sherpa_onnx-1.10.22-cp37-cp37m-macosx_11_0_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2bbaba6aef0e1a5a0b56400b56c4500253664338ce3e09bac9d57a60a27fbf5f |
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MD5 | 4c434db7c593bd41ef350061d9927ee4 |
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BLAKE2b-256 | a2e8a8c52f9838964573e5e00306ad8d33f19410732a9671e32de5e453c2e875 |
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Hashes for sherpa_onnx-1.10.22-cp37-cp37m-linux_armv7l.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 622dbcd48c02277cdcabb661b96e21be98d44b0bbcdb65ef8771753f4db67bb9 |
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MD5 | 523046444e3587d0b54196549ae47990 |
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BLAKE2b-256 | 07fa7bcfaa29384fb31c976a388f3e895bf9cc2bf5870908068f263992cd0fd4 |