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.

nodejs-examples/README.md

@@ -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.

nodejs-examples/test-offline-speaker-diarization.js

@@ -0,0 +1,64 @@
+// 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);