Zero-Shot Text-to-Speech for Vietnamese
This addresses the need for high-quality TTS resources in Vietnamese, though it is incremental as it applies existing methods to new data.
The paper tackles the problem of zero-shot text-to-speech for Vietnamese by introducing PhoAudiobook, a 941-hour dataset, and shows that it consistently enhances performance of models like VALL-E and VoiceCraft, with these models excelling in synthesizing short sentences.
This paper introduces PhoAudiobook, a newly curated dataset comprising 941 hours of high-quality audio for Vietnamese text-to-speech. Using PhoAudiobook, we conduct experiments on three leading zero-shot TTS models: VALL-E, VoiceCraft, and XTTS-V2. Our findings demonstrate that PhoAudiobook consistently enhances model performance across various metrics. Moreover, VALL-E and VoiceCraft exhibit superior performance in synthesizing short sentences, highlighting their robustness in handling diverse linguistic contexts. We publicly release PhoAudiobook to facilitate further research and development in Vietnamese text-to-speech.