nwhisper

nwhisper

Native Node.js bindings for OpenAI's Whisper using whisper.cpp. High-performance local speech-to-text with custom model path support.

Features

• Custom Model Path Support: Use your own trained models by providing a custom model file path
• Automatically convert the audio to WAV format with a 16000 Hz frequency to support the whisper model.
• Output transcripts to (.txt .srt .vtt .json .wts .lrc)
• Optimized for CPU (Including Apple Silicon ARM)
• Timestamp precision to single word
• Split on word rather than on token (Optional)
• Translate from source language to english (Optional)
• Convert audio format to wav to support whisper model
• Backward compatible with nodejs-whisper

Installation

• Install make tools

sudo apt update
sudo apt install build-essential

• Install nwhisper with npm

  npm i nwhisper

• Download whisper model (for standard models)

  npx nwhisper download

• NOTE: user may need to install make tool

Windows Installation

• Install MinGW-w64 or MSYS2 (which includes make tools)

  • Option 1: Install MSYS2 from https://www.msys2.org/
  • Option 2: Install MinGW-w64 from https://www.mingw-w64.org/

• Install nwhisper with npm

npm i nwhisper

• Download whisper model (for standard models)

npx nwhisper download

• Note: Make sure mingw32-make or make is available in your system PATH.

Usage/Examples

See example/basic.ts (can be run with $ npm run example)

import path from 'path'
import { transcribe } from 'nwhisper'

// Need to provide exact path to your audio file.
const filePath = path.resolve(__dirname, 'YourAudioFileName')

// Using standard model
await transcribe(filePath, {
  modelName: 'base.en', //Downloaded models name
  autoDownloadModelName: 'base.en', // (optional) auto download a model if model is not present
  removeWavFileAfterTranscription: false, // (optional) remove wav file once transcribed
  withCuda: false, // (optional) use cuda for faster processing
  logger: console, // (optional) Logging instance, defaults to console
  whisperOptions: {
    outputInCsv: false, // get output result in csv file
    outputInJson: false, // get output result in json file
    outputInJsonFull: false, // get output result in json file including more information
    outputInLrc: false, // get output result in lrc file
    outputInSrt: true, // get output result in srt file
    outputInText: false, // get output result in txt file
    outputInVtt: false, // get output result in vtt file
    outputInWords: false, // get output result in wts file for karaoke
    translateToEnglish: false, // translate from source language to english
    wordTimestamps: false, // word-level timestamps
    timestamps_length: 20, // amount of dialogue per timestamp pair
    splitOnWord: true, // split on word rather than on token
  },
})

// Using custom models (NEW FEATURES)
// Method 1: Specify model directory
const modelDir = path.join(process.cwd(), '.models')
await transcribe(filePath, {
  modelName: 'tiny.en',
  modelDir: modelDir,
  whisperOptions: {
    outputInSrt: true,
  },
})

// Method 2: Direct file path
const modelPath = path.join(__dirname, 'models', 'my-custom-model.bin')
await transcribe(filePath, {
  modelPath: modelPath,
  whisperOptions: {
    outputInSrt: true,
    language: 'en',
  },
})

// Method 3: Download to and use custom directory
await transcribe(filePath, {
  modelName: 'tiny.en',
  autoDownloadModelName: 'tiny.en',
  modelDir: path.join(__dirname, 'models'), // Download to and use this directory
  whisperOptions: {
    outputInSrt: true,
  },
})

// Model list
const MODELS_LIST = [
  'tiny',
  'tiny.en',
  'base',
  'base.en',
  'small',
  'small.en',
  'medium',
  'medium.en',
  'large-v1',
  'large',
  'large-v3-turbo',
]

Types

 interface IOptions {
  modelName?: string // Model name (works with directories)
  modelPath?: string // NEW: Direct path to model file
  modelDir?: string // NEW: Directory for models (download & use)
  autoDownloadModelName?: string // Model to auto-download
  removeWavFileAfterTranscription?: boolean
  withCuda?: boolean
  whisperOptions?: WhisperOptions
  logger?: Console
}

 interface WhisperOptions {
  outputInCsv?: boolean
  outputInJson?: boolean
  outputInJsonFull?: boolean
  outputInLrc?: boolean
  outputInSrt?: boolean
  outputInText?: boolean
  outputInVtt?: boolean
  outputInWords?: boolean
  translateToEnglish?: boolean
  timestamps_length?: number
  wordTimestamps?: boolean
  splitOnWord?: boolean
}

Custom Model Path Usage

The main feature of nwhisper is the ability to use custom model files. This is useful when you have:

• Fine-tuned models for specific domains
• Custom trained models
• Models in different locations than the default

Example with Custom Model

import { transcribe } from 'nwhisper'
import path from 'path'

// Method 1: Specify model directory
const modelDir = path.join(process.cwd(), '.models')
const result = await transcribe('audio.wav', {
  modelName: 'tiny.en',
  modelDir: modelDir,
  whisperOptions: {
    outputInSrt: true,
    language: 'en'
  }
})

// Method 2: Direct file path
const modelPath = path.join(__dirname, 'models', 'my-custom-model.bin')
const result2 = await transcribe('audio.wav', {
  modelPath: modelPath,
  whisperOptions: {
    outputInSrt: true,
    language: 'auto'
  }
})

// Method 3: Download to and use custom directory
const result3 = await transcribe('audio.wav', {
  modelName: 'tiny.en',
  autoDownloadModelName: 'tiny.en',
  modelDir: modelDir, // Download to and use this directory
  whisperOptions: {
    outputInSrt: true,
    language: 'auto'
  }
})

Model Priority

• modelPath - Direct file path (highest priority)
• modelDir + modelName - Model directory with model name
• Standard directory - Default whisper.cpp models (fallback)

Important Notes

• modelDir serves dual purpose: download location and model location
• When modelDir is specified, models are downloaded to and used from that directory
• Model files should follow whisper.cpp naming (e.g., ggml-tiny.en.bin)
• Models must be compatible with whisper.cpp format

Migration from nodejs-whisper

nwhisper is fully backward compatible with nodejs-whisper. Simply replace the package:

# Remove old package
npm uninstall nodejs-whisper

# Install nwhisper
npm install nwhisper

Function Names

• Recommended: Use transcribe function for new code
• Legacy: nodewhisper function is still available but deprecated

// New (recommended)
import { transcribe } from 'nwhisper'
await transcribe('audio.wav', { modelName: 'tiny.en' })

// Legacy (deprecated but still works)
import { nodewhisper } from 'nwhisper'
await nodewhisper('audio.wav', { modelName: 'tiny.en' })

No code changes required for existing functionality!

Run locally

Clone the project

  git clone https://github.com/teomyth/nwhisper

Go to the project directory

  cd nwhisper

Install dependencies

  npm install

Start the server

  npm run dev

Build project

  npm run build

Made with

• Whisper OpenAI (using C++ port by: ggerganov)

Feedback

If you have any feedback, please reach out to us at [e-mail]

Authors

• @teomyth - Current maintainer

Acknowledgments

This project is a fork of nodejs-whisper by @chetanXpro. We extend our gratitude to the original author for creating the foundation that made nwhisper possible.

Original Project

• Original Author: @chetanXpro
• Original Repository: nodejs-whisper
• License: MIT