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Previous works on expressive speech synthesis mainly focus on currentsentence. The context in adjacent sentences is neglected, resulting ininflexible speaking style for the same text, which lacks speech variations. Inthis paper, we propose a hierarchical framework to model speaking style fromcontext. A hierarchical context encoder is proposed to explore a wider range ofcontextual information considering structural relationship in context,including inter-phrase and inter-sentence relations. Moreover, to encouragethis encoder to learn style representation better, we introduce a noveltraining strategy with knowledge distillation, which provides the target forencoder training. Both objective and subjective evaluations on a Mandarinlecture dataset demonstrate that the proposed method can significantly improvethe naturalness and expressiveness of the synthesized speech.

Towards Expressive Speaking Style Modelling with Hierarchical Context Information for Mandarin Speech Synthesis