ParaTTS: Learning Linguistic and Prosodic Cross-sentence Information in Paragraph-based TTS. (arXiv:2209.06484v1 [cs.SD])

Recent advancements in neural end-to-end TTS models have shown high-quality,
natural synthesized speech in a conventional sentence-based TTS. However, it is
still challenging to reproduce similar high quality when a whole paragraph is
considered in TTS, where a large amount of contextual information needs to be
considered in building a paragraph-based TTS model. To alleviate the difficulty
in training, we propose to model linguistic and prosodic information by
considering cross-sentence, embedded structure in training. Three sub-modules,
including linguistics-aware, prosody-aware and …

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