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This paper presents an expressive speech synthesis architecture for modelingand controlling the speaking style at a word level. It attempts to learnword-level stylistic and prosodic representations of the speech data, with theaid of two encoders. The first one models style by finding a combination ofstyle tokens for each word given the acoustic features, and the second outputsa word-level sequence conditioned only on the phonetic information in order todisentangle it from the style information. The two encoder outputs are alignedand concatenated with the phoneme encoder outputs and then decoded with aNon-Attentive Tacotron model. An extra prior encoder is used to predict thestyle tokens autoregressively, in order for the model to be able to run withouta reference utterance. We find that the resulting model gives both word-leveland global control over the style, as well as prosody transfer capabilities.

Word-Level Style Control for Expressive, Non-attentive Speech Synthesis