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const express = require('express'); | |
const { jsonParser } = require('../express-common'); | |
const router = express.Router(); | |
/** | |
* Gets the audio data from a base64-encoded audio file. | |
* @param {string} audio Base64-encoded audio | |
* @returns {Float64Array} Audio data | |
*/ | |
function getWaveFile(audio) { | |
const wavefile = require('wavefile'); | |
const wav = new wavefile.WaveFile(); | |
wav.fromDataURI(audio); | |
wav.toBitDepth('32f'); | |
wav.toSampleRate(16000); | |
let audioData = wav.getSamples(); | |
if (Array.isArray(audioData)) { | |
if (audioData.length > 1) { | |
const SCALING_FACTOR = Math.sqrt(2); | |
// Merge channels (into first channel to save memory) | |
for (let i = 0; i < audioData[0].length; ++i) { | |
audioData[0][i] = SCALING_FACTOR * (audioData[0][i] + audioData[1][i]) / 2; | |
} | |
} | |
// Select first channel | |
audioData = audioData[0]; | |
} | |
return audioData; | |
} | |
router.post('/recognize', jsonParser, async (req, res) => { | |
try { | |
const TASK = 'automatic-speech-recognition'; | |
const { model, audio, lang } = req.body; | |
const module = await import('../transformers.mjs'); | |
const pipe = await module.default.getPipeline(TASK, model); | |
const wav = getWaveFile(audio); | |
const start = performance.now(); | |
const result = await pipe(wav, { language: lang || null, task: 'transcribe' }); | |
const end = performance.now(); | |
console.log(`Execution duration: ${(end - start) / 1000} seconds`); | |
console.log('Transcribed audio:', result.text); | |
return res.json({ text: result.text }); | |
} catch (error) { | |
console.error(error); | |
return res.sendStatus(500); | |
} | |
}); | |
router.post('/synthesize', jsonParser, async (req, res) => { | |
try { | |
const wavefile = require('wavefile'); | |
const TASK = 'text-to-speech'; | |
const { text, model, speaker } = req.body; | |
const module = await import('../transformers.mjs'); | |
const pipe = await module.default.getPipeline(TASK, model); | |
const speaker_embeddings = speaker | |
? new Float32Array(new Uint8Array(Buffer.from(speaker.startsWith('data:') ? speaker.split(',')[1] : speaker, 'base64')).buffer) | |
: null; | |
const start = performance.now(); | |
const result = await pipe(text, { speaker_embeddings: speaker_embeddings }); | |
const end = performance.now(); | |
console.log(`Execution duration: ${(end - start) / 1000} seconds`); | |
const wav = new wavefile.WaveFile(); | |
wav.fromScratch(1, result.sampling_rate, '32f', result.audio); | |
const buffer = wav.toBuffer(); | |
res.set('Content-Type', 'audio/wav'); | |
return res.send(Buffer.from(buffer)); | |
} catch (error) { | |
console.error(error); | |
return res.sendStatus(500); | |
} | |
}); | |
module.exports = { router }; | |