Controllable Prosody Generation With Partial Inputs
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Abstract (arXiv)
We address the problem of human-in-the-loop control for generating prosody in the context of text-to-speech synthesis. Controlling prosody is challenging because existing generative models lack an efficient interface through which users can modify the output quickly and precisely. To solve this, we introduce a novel framework whereby the user provides partial inputs and the generative model generates the missing features. We propose a model that is specifically designed to encode partial prosodic features and output complete audio. We show empirically that our model displays two essential qualities of a human-in-the-loop control mechanism: efficiency and robustness. With even a very small number of input values (~4), our model enables users to improve the quality of the output significantly in terms of listener preference (4:1).
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 16 of its 27 references that are in the map. First posted on arXiv 14 Mar 2023.
Builds on
16 of 27 references.
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4 more
- 2020CAMP: a Two-Stage Approach to Modelling Prosody in Contextcited by 12
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Citing papers per year: 2024: 1.
1 paper.
- 2024Which Prosodic Features Matter Most for Pragmatics?cited by 2
- 2024Which Prosodic Features Matter Most for Pragmatics?23 Aug 2024