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Celtia: Nos Project's Galician TTS Model

Model description

This model was trained from scratch using the Coqui TTS Python library on the corpus Nos_Celtia-GL.

A live inference demo can be found in our official page, here.

This model was trained using graphemes, so no preprocessing is needed for the input text.

Intended uses and limitations

You can use this model to generate synthetic speech in Galician.

How to use

Usage

Required libraries:

pip install TTS

Synthesize a speech using python:

import tempfile
import numpy as np
import os
import json

from typing import Optional
from TTS.config import load_config
from TTS.utils.manage import ModelManager
from TTS.utils.synthesizer import Synthesizer
model_path = # Absolute path to the model checkpoint.pth
config_path = # Absolute path to the model config.json
text = "Text to synthetize"
synthesizer = Synthesizer(
    model_path, config_path, None, None, None, None,
)
wavs = synthesizer.tts(text)

Training

Training Procedure

Data preparation

Hyperparameter

The model is based on VITS proposed by Kim et al. The following hyperparameters were set in the coqui framework.

Hyperparameter Value
Model vits
Batch Size 26
Eval Batch Size 16
Mixed Precision true
Window Length 1024
Hop Length 256
FTT size 1024
Num Mels 80
Phonemizer null
Phoneme Lenguage en-us
Text Cleaners multilingual_cleaners
Formatter nos_fonemas
Optimizer adam
Adam betas (0.8, 0.99)
Adam eps 1e-09
Adam weight decay 0.01
Learning Rate Gen 0.0002
Lr. schedurer Gen ExponentialLR
Lr. schedurer Gamma Gen 0.999875
Learning Rate Disc 0.0002
Lr. schedurer Disc ExponentialLR
Lr. schedurer Gamma Disc 0.999875

The model was trained for 457900 steps.

The nos_fonemas formatter is a modification of the LJSpeech formatter with one extra column for the normalized input (extended numbers and acronyms).

Additional information

Authors

Carmen Magariños

Contact information

For further information, send an email to proxecto.nos@usc.gal

Licensing Information

Apache License, Version 2.0

Funding

This research was funded by “The Nós project: Galician in the society and economy of Artificial Intelligence”, resulting from the agreement 2021-CP080 between the Xunta de Galicia and the University of Santiago de Compostela, and thanks to the Investigo program, within the National Recovery, Transformation and Resilience Plan, within the framework of the European Recovery Fund (NextGenerationEU).

Citation information

If you use this model, please cite as follows:

Magariños, Carmen. 2023. Nos_TTS-celtia-vits-graphemes. URL: https://huggingface.co/proxectonos/Nos_TTS-celtia-vits-graphemes

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