CML-TTS A Multilingual Dataset for Speech Synthesis in Low-Resource
  Languages
Frederico S. Oliveira Edresson Casanova Arnaldo Cândido Júnior Anderson S. Soares Arlindo R. Galvão Filho
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 hours from CML-TTS and also with 245.07 hours 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 license1.