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arXiv · 2211.02336

Improving Speech Prosody of Audiobook Text-to-Speech Synthesis with Acoustic and Textual Contexts

Detai Xin·Sharath Adavanne·Federico Ang·Ashish Kulkarni·Shinnosuke Takamichi·Hiroshi Saruwatari
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Abstract

We present a multi-speaker Japanese audiobook text-to-speech (TTS) system that leverages multimodal context information of preceding acoustic context and bilateral textual context to improve the prosody of synthetic speech. Previous work either uses unilateral or single-modality context, which does not fully represent the context information. The proposed method uses an acoustic context encoder and a textual context encoder to aggregate context information and feeds it to the TTS model, which enables the model to predict context-dependent prosody. We conducted comprehensive objective and subjective evaluations on a multi-speaker Japanese audiobook dataset. Experimental results demonstrate that the proposed method significantly outperforms two previous works. Additionally, we present insights about the different choices of context - modalities, lateral information and length - for audiobook TTS that have never been discussed in the literature before.

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Detai Xin, Sharath Adavanne, Federico Ang, Ashish Kulkarni, Shinnosuke Takamichi, Hiroshi Saruwatari. 2022-11-04. Improving Speech Prosody of Audiobook Text-to-Speech Synthesis with Acoustic and Textual Contexts. https://arxiv.org/abs/2211.02336

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