Text-to-speech system for low-resource language using cross-lingual transfer learning and data augmentation

Abstract Deep learning techniques are currently being applied in automated text-to-speech (TTS) systems, resulting in significant improvements in performance. However, these methods require large amounts of text-speech paired data for model training, and collecting this data is costly. Therefore, in...

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Autores principales:	Zolzaya Byambadorj, Ryota Nishimura, Altangerel Ayush, Kengo Ohta, Norihide Kitaoka
Formato:	article
Lenguaje:	EN
Publicado:	SpringerOpen 2021
Materias:	Speech synthesis Text to speech Transfer learning Data augmentation Low-resource language Acoustics. Sound QC221-246 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/84f582599e30418fa5395ab20605d377
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Text-to-speech system for low-resource language using cross-lingual transfer learning and data augmentation

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