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In the existing cross-speaker style transfer task, a source speaker withmulti-style recordings is necessary to provide the style for a target speaker.However, it is hard for one speaker to express all expected styles. In thispaper, a more general task, which is to produce expressive speech by combiningany styles and timbres from a multi-speaker corpus in which each speaker has aunique style, is proposed. To realize this task, a novel method is proposed.This method is a Tacotron2-based framework but with a fine-grained text-basedprosody predicting module and a speaker identity controller. Experimentsdemonstrate that the proposed method can successfully express a style of onespeaker with the timber of another speaker bypassing the dependency on a singlespeaker's multi-style corpus. Moreover, the explicit prosody features used inthe prosody predicting module can increase the diversity of synthetic speech byadjusting the value of prosody features.

Multi-speaker Multi-style Text-to-speech Synthesis With Single-speaker Single-style Training Data Scenarios