supertonic/nodejs/example_onnx.js

import fs from 'fs';
import path from 'path';
import { fileURLToPath } from 'url';

import { loadTextToSpeech, loadVoiceStyle, timer, writeWavFile } from './helper.js';

const __filename = fileURLToPath(import.meta.url);
const __dirname = path.dirname(__filename);

/**
 * Parse command line arguments
 */
function parseArgs() {
    const args = {
        useGpu: false,
        onnxDir: 'assets/onnx',
        totalStep: 5,
        nTest: 4,
        voiceStyle: ['assets/voice_styles/M1.json'],
        text: ['This morning, I took a walk in the park, and the sound of the birds and the breeze was so pleasant that I stopped for a long time just to listen.'],
        saveDir: 'results',
        batch: false
    };

    for (let i = 2; i < process.argv.length; i++) {
        const arg = process.argv[i];
        if (arg === '--use-gpu') {
            args.useGpu = true;
        } else if (arg === '--batch') {
            args.batch = true;
        } else if (arg === '--onnx-dir' && i + 1 < process.argv.length) {
            args.onnxDir = process.argv[++i];
        } else if (arg === '--total-step' && i + 1 < process.argv.length) {
            args.totalStep = parseInt(process.argv[++i]);
        } else if (arg === '--n-test' && i + 1 < process.argv.length) {
            args.nTest = parseInt(process.argv[++i]);
        } else if (arg === '--voice-style' && i + 1 < process.argv.length) {
            args.voiceStyle = process.argv[++i].split(',');
        } else if (arg === '--text' && i + 1 < process.argv.length) {
            args.text = process.argv[++i].split('|');
        } else if (arg === '--save-dir' && i + 1 < process.argv.length) {
            args.saveDir = process.argv[++i];
        }
    }

    return args;
}

/**
 * Main inference function
 */
async function main() {
    console.log('=== TTS Inference with ONNX Runtime (Node.js) ===\n');

    // --- 1. Parse arguments --- //
    const args = parseArgs();
    const totalStep = args.totalStep;
    const nTest = args.nTest;
    const saveDir = args.saveDir;
    const voiceStylePaths = args.voiceStyle.map(p => path.resolve(__dirname, p));
    const textList = args.text;
    const batch = args.batch;

    if (voiceStylePaths.length !== textList.length) {
        throw new Error(`Number of voice styles (${voiceStylePaths.length}) must match number of texts (${textList.length})`);
    }
    const bsz = voiceStylePaths.length;

    // --- 2. Load Text to Speech --- //
    const onnxDir = path.resolve(__dirname, args.onnxDir);
    const textToSpeech = await loadTextToSpeech(onnxDir, args.useGpu);

    // --- 3. Load Voice Style --- //
    const style = loadVoiceStyle(voiceStylePaths, true);

    // --- 4. Synthesize speech --- //
    for (let n = 0; n < nTest; n++) {
        console.log(`\n[${n + 1}/${nTest}] Starting synthesis...`);
        
        const { wav, duration } = await timer('Generating speech from text', async () => {
            if (batch) {
                return await textToSpeech.batch(textList, style, totalStep);
            } else {
                return await textToSpeech.call(textList[0], style, totalStep);
            }
        });
        
        if (!fs.existsSync(saveDir)) {
            fs.mkdirSync(saveDir, { recursive: true });
        }

        const wavShape = [bsz, wav.length / bsz];
        for (let b = 0; b < bsz; b++) {
            const fname = `${textList[b].substring(0, 20).replace(/[^a-zA-Z0-9]/g, '_')}_${n + 1}.wav`;
            const wavLen = Math.floor(textToSpeech.sampleRate * duration[b]);
            const wavOut = wav.slice(b * wavShape[1], b * wavShape[1] + wavLen);
            
            const outputPath = path.join(saveDir, fname);
            writeWavFile(outputPath, wavOut, textToSpeech.sampleRate);
            console.log(`Saved: ${outputPath}`);
        }
    }

    console.log('\n=== Synthesis completed successfully! ===');
}

// Run main function
main().catch(err => {
    console.error('Error during inference:', err);
    process.exit(1);
});