@maia-id/maleo

MALEO: Multi Platform Speaker Diarization

A JavaScript library for speaker diarization - the process of partitioning an audio stream into segments according to speaker identity.

Features

• Audio preprocessing with customizable options
• CPU, GPU, WebGPU, and WASM support
• Progress tracking during inference
• Flexible audio input handling
• Silence removal and audio normalization capabilities

Prerequisites

GPU Support

If you plan to use GPU acceleration, ensure you have the required CUDA libraries installed:

libcublasLt.so.12

For CUDA installation instructions, refer to the NVIDIA cuDNN Installation Guide.

Installation

npm install @maia-id/maleo

Usage

Basic Example

import { SpeakerDiarization } from 'speaker-diarization';

// Example usage
const example = async () => {
    const speakerDiarization = new SpeakerDiarization();
    const result = await speakerDiarization.inference({
        audio: './examples/audio.wav',  // File path for Node.js
        language: 'en',
        device: 'cpu', // Device support : 'cpu', 'cuda', 'webgpu', or 'wasm'
        audioOptions: {
            targetSampleRate: 16000,
            normalizeAudio: true,
            removeSilence: true,
            silenceThreshold: -50,
        },
        progress_callback: (progress) => console.log('Progress:', progress)
    });

    console.table(result.segments);
};

example();

Running the Example

node examples/inference.js

Configuration Options

Audio Options

Option	Type	Default	Description
targetSampleRate	number	16000	Target sample rate for audio processing
normalizeAudio	boolean	true	Whether to normalize audio amplitude
removeSilence	boolean	true	Whether to remove silence segments
silenceThreshold	number	-50	Threshold (in dB) for silence detection

Inference Options

Option	Type	Description
audio	string	Path to the audio file
device	'cpu' | 'cuda' | 'webgpu' | 'wasm'	Processing device to use
progress_callback	function	Callback for tracking progress

Output Format

The inference method returns a result object containing segments with the following structure:

interface Segment {
    start: number;      // Start time in seconds
    end: number;        // End time in seconds
    speaker: string;    // Speaker identifier
    confidence: number; // Confidence score
}

Citation

If you use this library in your research, please cite:

@inproceedings{irawan2025cross,
  title = {Cross-Platform Speaker Diarization: Evaluating the Scalability of Maleo},
  author = {Eka Tresna Irawan and Ardi Mardiana and Dedy Hariyadi and I Putu Agus Eka Pratama},
  booktitle = {International Conference on Discoveries in Applied Sciences & Advanced Technology 2025},
  year = {2025}
}

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Acknowledgments

• NVIDIA for CUDA support