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arXiv · 2204.02743

Towards Multi-Scale Speaking Style Modelling with Hierarchical Context Information for Mandarin Speech Synthesis

Shun Lei·Yixuan Zhou·Liyang Chen·Jiankun Hu·Zhiyong Wu·Shiyin Kang·Helen Meng
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Abstract

Previous works on expressive speech synthesis focus on modelling the mono-scale style embedding from the current sentence or context, but the multi-scale nature of speaking style in human speech is neglected. In this paper, we propose a multi-scale speaking style modelling method to capture and predict multi-scale speaking style for improving the naturalness and expressiveness of synthetic speech. A multi-scale extractor is proposed to extract speaking style embeddings at three different levels from the ground-truth speech, and explicitly guide the training of a multi-scale style predictor based on hierarchical context information. Both objective and subjective evaluations on a Mandarin audiobooks dataset demonstrate that our proposed method can significantly improve the naturalness and expressiveness of the synthesized speech.

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Shun Lei, Yixuan Zhou, Liyang Chen, Jiankun Hu, Zhiyong Wu, Shiyin Kang, Helen Meng. 2022-04-06. Towards Multi-Scale Speaking Style Modelling with Hierarchical Context Information for Mandarin Speech Synthesis. https://arxiv.org/abs/2204.02743

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