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- W4375868833 abstract "Some recent models for Text-to-Speech synthesis aim to transfer the prosody of a reference utterance to the generated target synthetic speech. This is done by using a learned embedding of the reference utterance, which is used to condition speech generation. During training, the reference utterance is identical to the target utterance. Yet, during synthesis, these models are often used to transfer prosody from a reference that differs from the text or speaker being synthesized.To address this inconsistency, we propose to use a different, but prosodically-related, utterance during training too. We believe this should encourage the model to learn to transfer only those characteristics that the reference and target have in common. If prosody transfer methods do indeed transfer prosody they should be able to be trained in the way we propose. However, results show that a model trained under these conditions performs significantly worse than one trained using the target utterance as a reference. To explain this, we hypothesize that prosody transfer models do not learn a transferable representation of prosody, but rather a utterance-level representation which is highly dependent on both the reference speaker and reference text." @default.
- W4375868833 created "2023-05-10" @default.
- W4375868833 creator A5062516688 @default.
- W4375868833 creator A5070862331 @default.
- W4375868833 date "2023-06-04" @default.
- W4375868833 modified "2023-09-27" @default.
- W4375868833 title "Do Prosody Transfer Models Transfer Prosodyƒ" @default.
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- W4375868833 doi "https://doi.org/10.1109/icassp49357.2023.10095131" @default.
- W4375868833 hasPublicationYear "2023" @default.
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