CML-TTS: A Multilingual Dataset for Speech Synthesis in Low-Resource Languages
Frederico Santos de Oliveira, Edresson Casanova, Arnaldo Cândido, Anderson S. Soares, Arlindo Rodrigues Galvão Filho · Lecture notes in computer science · 2023
In this paper, we present CML-TTS, a recursive acronym for CML-Multi-Lingual-TTS, a new Text-to-Speech (TTS) dataset developed at the Center of Excellence in Artificial Intelligence (CEIA) of the Federal University of Goias (UFG). CML-TTS is based on Multilingual LibriSpeech (MLS) and adapted for training TTS models, consisting of audiobooks in seven languages: Dutch, French, German, Italian, Portuguese, Polish, and Spanish. Additionally, we provide the YourTTS model, a multi-lingual TTS model, trained using 3,176.13 h from CML-TTS and also with 245.07 h from LibriTTS, in English. Our purpose in creating this dataset is to open up new research possibilities in the TTS area for multi-lingual models. The dataset is publicly available under the CC-BY 4.0 license ( https://freds0.github.io/CML-TTS-Dataset ).