This is an addon demo that can perform whisper model reasoning in node and electron environments, based on cmake-js. It can be used as a reference for using the whisper.cpp project in other node projects.

This addon now supports Voice Activity Detection (VAD) for improved transcription performance.

npm install

Make sure it is in the project root directory and compiled with make-js.

npx cmake-js compile -T addon.node -B Release

For Electron addon and cmake-js options, you can see cmake-js and make very few configuration changes.

Such as appointing special cmake path:

npx cmake-js compile -c 'xxx/cmake' -T addon.node -B Release

cd examples/addon.node

node index.js --language='language' --model='model-path' --fname_inp='file-path'

Run the VAD example with performance comparison:

node vad-example.js

VAD can significantly improve transcription performance by only processing speech segments, which is especially beneficial for audio files with long periods of silence.

Before using VAD, download a VAD model:

# From the whisper.cpp root directory
./models/download-vad-model.sh silero-v6.2.0

All VAD parameters are optional and have sensible defaults:

• vad: Enable VAD (default: false)
• vad_model: Path to VAD model file (required when VAD enabled)
• vad_threshold: Speech detection threshold 0.0-1.0 (default: 0.5)
• vad_min_speech_duration_ms: Min speech duration in ms (default: 250)
• vad_min_silence_duration_ms: Min silence duration in ms (default: 100)
• vad_max_speech_duration_s: Max speech duration in seconds (default: FLT_MAX)
• vad_speech_pad_ms: Speech padding in ms (default: 30)
• vad_samples_overlap: Sample overlap 0.0-1.0 (default: 0.1)

const path = require("path");
const { whisper } = require(path.join(__dirname, "../../build/Release/addon.node"));
const { promisify } = require("util");

const whisperAsync = promisify(whisper);

// With VAD enabled
const vadParams = {
  language: "en",
  model: path.join(__dirname, "../../models/ggml-base.en.bin"),
  fname_inp: path.join(__dirname, "../../samples/jfk.wav"),
  vad: true,
  vad_model: path.join(__dirname, "../../models/ggml-silero-v6.2.0.bin"),
  vad_threshold: 0.5,
  progress_callback: (progress) => console.log(`Progress: ${progress}%`)
};

whisperAsync(vadParams).then(result => console.log(result));

Both traditional whisper.cpp parameters and new VAD parameters are supported:

• language: Language code (e.g., "en", "es", "fr")
• model: Path to whisper model file
• fname_inp: Path to input audio file
• use_gpu: Enable GPU acceleration (default: true)
• flash_attn: Enable flash attention (default: false)
• no_prints: Disable console output (default: false)
• no_timestamps: Disable timestamps (default: false)
• detect_language: Auto-detect language (default: false)
• audio_ctx: Audio context size (default: 0)
• max_len: Maximum segment length (default: 0)
• max_context: Maximum context size (default: -1)
• prompt: Initial prompt for decoder
• comma_in_time: Use comma in timestamps (default: true)
• print_progress: Print progress info (default: false)
• progress_callback: Progress callback function
• VAD parameters (see above section)