@valoric/whisper-node NPM

whisper-node

Node.js bindings for OpenAI's Whisper. Transcription done local.

Features

Output transcripts to JSON (also .txt .srt .vtt)
Optimized for CPU (Including Apple Silicon ARM)
Timestamp precision to single word

Installation

Add dependency to project

npm install whisper-node

Download whisper model of choice OPTIONAL

npx whisper-node download

Requirement for Windows: Install the make command from here.

Usage

import whisper from 'whisper-node';

const transcript = await whisper("example/sample.wav");

console.log(transcript); // output: [ {start,end,speech} ]

Output (JSON)

[
  {
    "start":  "00:00:14.310", // time stamp begin
    "end":    "00:00:16.480", // time stamp end
    "speech": "howdy"         // transcription
  }
]

Full Options List

import whisper from 'whisper-node';

const filePath = "example/sample.wav"; // required

const options = {
  modelName: "base.en",       // default
  // modelPath: "/custom/path/to/model.bin", // use model in a custom directory (cannot use along with 'modelName')
  whisperOptions: {
    language: 'auto'          // default (use 'auto' for auto detect)
    gen_file_txt: false,      // outputs .txt file
    gen_file_subtitle: false, // outputs .srt file
    gen_file_vtt: false,      // outputs .vtt file
    word_timestamps: true     // timestamp for every word
    // timestamp_size: 0      // cannot use along with word_timestamps:true
  }
}

const transcript = await whisper(filePath, options);

Input File Format

Files must be .wav and 16Hz

Example .mp3 file converted with an FFmpeg command: ffmpeg -i input.mp3 -ar 16000 output.wav

Made with

Roadmap

Support projects not using Typescript
Allow custom directory for storing models
Config files as alternative to model download cli
Remove path, shelljs and prompt-sync package for browser, react-native expo, and webassembly compatibility
fluent-ffmpeg to automatically convert to 16Hz .wav files as well as support separating audio from video
Pyanote diarization for speaker names
Implement WhisperX as optional alternative model for diarization and higher precision timestamps (as alternative to C++ version)
Add option for viewing detected langauge as described in Issue 16
Include typescript typescript types in d.ts file
Add support for language option
Add support for transcribing audio streams as already implemented in whisper.cpp