|
--- |
|
library_name: transformers |
|
pipeline_tag: text-to-speech |
|
tags: |
|
- transformers.js |
|
- mms |
|
- vits |
|
license: cc-by-nc-4.0 |
|
datasets: |
|
- ylacombe/google-chilean-spanish |
|
language: |
|
- es |
|
--- |
|
|
|
## Model |
|
|
|
This is a finetuned version of the [Spanish version](https://huggingface.co/facebook/mms-tts-spa) of Massively Multilingual Speech (MMS) models, which are light-weight, low-latency TTS models based on the [VITS architecture](https://huggingface.co/docs/transformers/model_doc/vits). |
|
|
|
It was trained in around **20 minutes** with as little as **80 to 150 samples**, on this [Chilean Spanish dataset](https://huggingface.co/datasets/ylacombe/google-chilean-spanish). |
|
|
|
Training recipe available in this [github repository: **ylacombe/finetune-hf-vits**](https://github.com/ylacombe/finetune-hf-vits). |
|
|
|
|
|
## Usage |
|
|
|
### Transformers |
|
|
|
```python |
|
from transformers import pipeline |
|
import scipy |
|
|
|
model_id = "ylacombe/mms-spa-finetuned-chilean-monospeaker" |
|
synthesiser = pipeline("text-to-speech", model_id) # add device=0 if you want to use a GPU |
|
|
|
speech = synthesiser("Hola, ¿cómo estás hoy?") |
|
|
|
scipy.io.wavfile.write("finetuned_output.wav", rate=speech["sampling_rate"], data=speech["audio"]) |
|
``` |
|
|
|
### Transformers.js |
|
|
|
If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@xenova/transformers) using: |
|
```bash |
|
npm i @xenova/transformers |
|
``` |
|
|
|
**Example:** Generate Spanish speech with `ylacombe/mms-spa-finetuned-chilean-monospeaker`. |
|
```js |
|
import { pipeline } from '@xenova/transformers'; |
|
|
|
// Create a text-to-speech pipeline |
|
const synthesizer = await pipeline('text-to-speech', 'ylacombe/mms-spa-finetuned-chilean-monospeaker', { |
|
quantized: false, // Remove this line to use the quantized version (default) |
|
}); |
|
|
|
// Generate speech |
|
const output = await synthesizer('Hola, ¿cómo estás hoy?'); |
|
console.log(output); |
|
// { |
|
// audio: Float32Array(69888) [ ... ], |
|
// sampling_rate: 16000 |
|
// } |
|
``` |
|
|
|
Optionally, save the audio to a wav file (Node.js): |
|
```js |
|
import wavefile from 'wavefile'; |
|
import fs from 'fs'; |
|
|
|
const wav = new wavefile.WaveFile(); |
|
wav.fromScratch(1, output.sampling_rate, '32f', output.audio); |
|
fs.writeFileSync('out.wav', wav.toBuffer()); |
|
``` |
|
|
|
|
|
<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/6FvN6zFSHGeenWS2-H8xv.wav"></audio> |