Papers by Neha S
ParrotTTS: Text-to-speech synthesis exploiting disentangled self-supervised representations (2024.findings-eacl)
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| Challenge: | ParrotTTS can train a multi-speaker variant using transcripts from a single speaker in low resource setup and generalizes to languages not seen while training the self-supervised backbone. |
| Approach: | They propose a modular text-to-speech synthesis model that can train a multi-speaker variant using transcripts from a single speaker. |
| Outcome: | The proposed model outperforms state-of-the-art multi-lingual text-to-speech models using only a fraction of paired data as latter. |