What's new?

🗣️ New task: Text to speech/audio

Due to popular demand, we've added text-to-speech support to Transformers.js! 😍

You can get started in just a few lines of code!

import { pipeline } from '@xenova/transformers';

let speaker_embeddings = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/speaker_embeddings.bin';
let synthesizer = await pipeline('text-to-speech', 'Xenova/speecht5_tts', { quantized: false });
let out = await synthesizer('Hello, my dog is cute', { speaker_embeddings });
// {
//   audio: Float32Array(26112) [-0.00005657337896991521, 0.00020583874720614403, ...],
//   sampling_rate: 16000
// }

You can then save the audio to a .wav file with the wavefile package:

import wavefile from 'wavefile';
import fs from 'fs';

let wav = new wavefile.WaveFile();
wav.fromScratch(1, out.sampling_rate, '32f', out.audio);
fs.writeFileSync('out.wav', wav.toBuffer());

Alternatively, you can play the file in your browser (see below).

Don't like the speaker's voice? Well, you can choose another from the >7000 speaker embeddings in the CMU Arctic dataset (see here)!

Note: currently, we only support TTS w/ speecht5, but in future we'll add others like bark and MMS!

🖥️ TTS demo and example app

To showcase the power of in-browser TTS, we're also releasing a simple example app (demo, code). Feel free to make improvements to it... and if you do (or end up building your own), please tag me on Twitter! 🤗

Misc. changes

• Update falcon tokenizer in #344
• Add more links to example section in #343
• Improve electron example template in #342
• Update example app dependencies in #347
• Do not post-process < and > symbols generated from docs in #335

Full Changelog: 2.6.2...2.7.0