CML-TTS A Multilingual Dataset for Speech Synthesis in Low-Resource Languages

• URL: http://arxiv.org/abs/2306.10097v1
• Date: Fri, 16 Jun 2023 17:17:06 GMT
• Title: CML-TTS A Multilingual Dataset for Speech Synthesis in Low-Resource Languages
• Authors: Frederico S. Oliveira, Edresson Casanova, Arnaldo C\^andido J\'unior, Anderson S. Soares, and Arlindo R. Galv\~ao Filho
• Abstract summary: CML-TTS is 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. 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.
• Score: 0.769672852567215
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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.

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