Fangjun Kuang
Committed by GitHub

JavaScript API with WebAssembly for speaker diarization (#1414)

#1408 uses [node-addon-api](https://github.com/nodejs/node-addon-api) to call C API from JavaScript, whereas this pull request uses WebAssembly to call C API from JavaScript.
... ... @@ -9,6 +9,18 @@ git status
ls -lh
ls -lh node_modules
echo '-----speaker diarization----------'
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speaker-segmentation-models/sherpa-onnx-pyannote-segmentation-3-0.tar.bz2
tar xvf sherpa-onnx-pyannote-segmentation-3-0.tar.bz2
rm sherpa-onnx-pyannote-segmentation-3-0.tar.bz2
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speaker-recongition-models/3dspeaker_speech_eres2net_base_sv_zh-cn_3dspeaker_16k.onnx
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speaker-segmentation-models/0-four-speakers-zh.wav
node ./test-offline-speaker-diarization.js
rm -rfv *.wav *.onnx sherpa-onnx-pyannote-*
echo '-----vad+whisper----------'
curl -LS -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-whisper-tiny.en.tar.bz2
... ...
... ... @@ -139,7 +139,7 @@ jobs:
export PATH=/c/hostedtoolcache/windows/Python/3.9.13/x64/bin:$PATH
export PATH=/c/hostedtoolcache/windows/Python/3.10.11/x64/bin:$PATH
export PATH=/c/hostedtoolcache/windows/Python/3.11.9/x64/bin:$PATH
export PATH=/c/hostedtoolcache/windows/Python/3.12.6/x64/bin:$PATH
export PATH=/c/hostedtoolcache/windows/Python/3.12.7/x64/bin:$PATH
which sherpa-onnx
sherpa-onnx --help
... ...
... ... @@ -104,7 +104,7 @@ jobs:
export PATH=/c/hostedtoolcache/windows/Python/3.9.13/x64/bin:$PATH
export PATH=/c/hostedtoolcache/windows/Python/3.10.11/x64/bin:$PATH
export PATH=/c/hostedtoolcache/windows/Python/3.11.9/x64/bin:$PATH
export PATH=/c/hostedtoolcache/windows/Python/3.12.6/x64/bin:$PATH
export PATH=/c/hostedtoolcache/windows/Python/3.12.7/x64/bin:$PATH
sherpa-onnx --help
sherpa-onnx-keyword-spotter --help
... ...
... ... @@ -22,6 +22,22 @@ In the following, we describe how to use [sherpa-onnx](https://github.com/k2-fsa
for text-to-speech and speech-to-text.
# Speaker diarization
In the following, we demonstrate how to run speaker diarization.
```bash
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speaker-segmentation-models/sherpa-onnx-pyannote-segmentation-3-0.tar.bz2
tar xvf sherpa-onnx-pyannote-segmentation-3-0.tar.bz2
rm sherpa-onnx-pyannote-segmentation-3-0.tar.bz2
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speaker-recongition-models/3dspeaker_speech_eres2net_base_sv_zh-cn_3dspeaker_16k.onnx
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speaker-segmentation-models/0-four-speakers-zh.wav
node ./test-offline-speaker-diarization.js
```
# Text-to-speech
In the following, we demonstrate how to run text-to-speech.
... ...
// Copyright (c) 2024 Xiaomi Corporation
const sherpa_onnx = require('sherpa-onnx');
// clang-format off
/* Please use the following commands to download files
used in this script
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speaker-segmentation-models/sherpa-onnx-pyannote-segmentation-3-0.tar.bz2
tar xvf sherpa-onnx-pyannote-segmentation-3-0.tar.bz2
rm sherpa-onnx-pyannote-segmentation-3-0.tar.bz2
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speaker-recongition-models/3dspeaker_speech_eres2net_base_sv_zh-cn_3dspeaker_16k.onnx
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speaker-segmentation-models/0-four-speakers-zh.wav
*/
// clang-format on
const config = {
segmentation: {
pyannote: {
model: './sherpa-onnx-pyannote-segmentation-3-0/model.onnx',
debug: 1,
},
},
embedding: {
model: './3dspeaker_speech_eres2net_base_sv_zh-cn_3dspeaker_16k.onnx',
debug: 1,
},
clustering: {
// since we know that the test wave file
// ./0-four-speakers-zh.wav contains 4 speakers, we use 4 for numClusters
// here. if you don't have such information, please set numClusters to -1
numClusters: 4,
// If numClusters is not -1, then threshold is ignored.
//
// A larger threshold leads to fewer clusters, i.e., fewer speakers
// A smaller threshold leads to more clusters, i.e., more speakers
// You need to tune it by yourself.
threshold: 0.5,
},
// If a segment is shorter than minDurationOn, we discard it
minDurationOn: 0.2, // in seconds
// If the gap between two segments is less than minDurationOff, then we
// merge these two segments into a single one
minDurationOff: 0.5, // in seconds
};
const waveFilename = './0-four-speakers-zh.wav';
const sd = sherpa_onnx.createOfflineSpeakerDiarization(config);
console.log('Started')
const wave = sherpa_onnx.readWave(waveFilename);
if (sd.sampleRate != wave.sampleRate) {
throw new Error(
`Expected sample rate: ${sd.sampleRate}, given: ${wave.sampleRate}`);
}
const segments = sd.process(wave.samples);
console.log(segments);
... ...
... ... @@ -7,6 +7,8 @@ const sherpa_onnx_tts = require('./sherpa-onnx-tts.js');
const sherpa_onnx_kws = require('./sherpa-onnx-kws.js');
const sherpa_onnx_wave = require('./sherpa-onnx-wave.js');
const sherpa_onnx_vad = require('./sherpa-onnx-vad.js');
const sherpa_onnx_speaker_diarization =
require('./sherpa-onnx-speaker-diarization.js');
function createOnlineRecognizer(config) {
return sherpa_onnx_asr.createOnlineRecognizer(wasmModule, config);
... ... @@ -32,6 +34,11 @@ function createVad(config) {
return sherpa_onnx_vad.createVad(wasmModule, config);
}
function createOfflineSpeakerDiarization(config) {
return sherpa_onnx_speaker_diarization.createOfflineSpeakerDiarization(
wasmModule, config);
}
function readWave(filename) {
return sherpa_onnx_wave.readWave(filename, wasmModule);
}
... ... @@ -51,4 +58,5 @@ module.exports = {
writeWave,
createCircularBuffer,
createVad,
createOfflineSpeakerDiarization,
};
... ...
... ... @@ -70,6 +70,17 @@ set(exported_functions
SherpaOnnxDestroySpeechSegment
SherpaOnnxVoiceActivityDetectorReset
SherpaOnnxVoiceActivityDetectorFlush
# Speaker diarization
SherpaOnnxCreateOfflineSpeakerDiarization
SherpaOnnxDestroyOfflineSpeakerDiarization
SherpaOnnxOfflineSpeakerDiarizationDestroyResult
SherpaOnnxOfflineSpeakerDiarizationDestroySegment
SherpaOnnxOfflineSpeakerDiarizationGetSampleRate
SherpaOnnxOfflineSpeakerDiarizationProcess
SherpaOnnxOfflineSpeakerDiarizationProcessWithCallback
SherpaOnnxOfflineSpeakerDiarizationResultGetNumSegments
SherpaOnnxOfflineSpeakerDiarizationResultSortByStartTime
SherpaOnnxOfflineSpeakerDiarizationSetConfig
#
SherpaOnnxFileExists
SherpaOnnxReadWave
... ... @@ -109,6 +120,7 @@ install(
${CMAKE_SOURCE_DIR}/wasm/tts/sherpa-onnx-tts.js
${CMAKE_SOURCE_DIR}/wasm/kws/sherpa-onnx-kws.js
${CMAKE_SOURCE_DIR}/wasm/vad/sherpa-onnx-vad.js
${CMAKE_SOURCE_DIR}/wasm/speaker-diarization/sherpa-onnx-speaker-diarization.js
${CMAKE_SOURCE_DIR}/wasm/nodejs/sherpa-onnx-wave.js
"$<TARGET_FILE_DIR:sherpa-onnx-wasm-nodejs>/sherpa-onnx-wasm-nodejs.js"
"$<TARGET_FILE_DIR:sherpa-onnx-wasm-nodejs>/sherpa-onnx-wasm-nodejs.wasm"
... ...
... ... @@ -12,7 +12,6 @@ Remember to rename the downloaded files.
The following is an example.
```bash
cd wasm/speaker-diarization/assets/
... ... @@ -22,9 +21,6 @@ rm sherpa-onnx-pyannote-segmentation-3-0.tar.bz2
cp sherpa-onnx-pyannote-segmentation-3-0/model.onnx ./segmentation.onnx
rm -rf sherpa-onnx-pyannote-segmentation-3-0
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speaker-recongition-models/3dspeaker_speech_eres2net_base_sv_zh-cn_3dspeaker_16k.onnx
mv 3dspeaker_speech_eres2net_base_sv_zh-cn_3dspeaker_16k.onnx ./embedding.onnx
```
... ...
... ... @@ -64,7 +64,7 @@ function initSherpaOnnxOfflineSpeakerSegmentationModelConfig(config, Module) {
Module.setValue(ptr + offset, config.numThreads || 1, 'i32');
offset += 4;
Module.setValue(ptr + offset, config.debug || 1, 'i32');
Module.setValue(ptr + offset, config.debug || 0, 'i32');
offset += 4;
const providerLen = Module.lengthBytesUTF8(config.provider || 'cpu') + 1;
... ... @@ -103,7 +103,7 @@ function initSherpaOnnxSpeakerEmbeddingExtractorConfig(config, Module) {
Module.setValue(ptr + offset, config.numThreads || 1, 'i32');
offset += 4;
Module.setValue(ptr + offset, config.debug || 1, 'i32');
Module.setValue(ptr + offset, config.debug || 0, 'i32');
offset += 4;
Module.setValue(ptr + offset, buffer + modelLen, 'i8*');
... ... @@ -270,11 +270,15 @@ class OfflineSpeakerDiarization {
}
function createOfflineSpeakerDiarization(Module, myConfig) {
const config = {
let config = {
segmentation: {
pyannote: {model: './segmentation.onnx'},
debug: 1,
},
embedding: {
model: './embedding.onnx',
debug: 1,
},
embedding: {model: './embedding.onnx'},
clustering: {numClusters: -1, threshold: 0.5},
minDurationOn: 0.3,
minDurationOff: 0.5,
... ...