9 citations · 9 across the 2 of their papers we have counts for
10 papers
ADEPT: A Dataset for Evaluating Prosody Transfer
Alexandra Torresquintero, Tian Huey Teh, Christopher G. R. Wallis +6
Text-to-speech is now able to achieve near-human naturalness and research focus has shifted to increasing expressivity. One popular method is to transfer the prosody from a referen…
Ctrl-P: Temporal Control of Prosodic Variation for Speech Synthesis
Devang S Ram Mohan, Vivian Hu, Tian Huey Teh +6
Text does not fully specify the spoken form, so text-to-speech models must be able to learn from speech data that vary in ways not explained by the corresponding text. One way to r…
Using previous acoustic context to improve Text-to-Speech synthesis
Pilar Oplustil-Gallegos, Simon King
Many speech synthesis datasets, especially those derived from audiobooks, naturally comprise sequences of utterances. Nevertheless, such data are commonly treated as individual, un…
An Overview of Voice Conversion and its Challenges: From Statistical Modeling to Deep Learning
Berrak Sisman, Junichi Yamagishi, Simon King +1
Speaker identity is one of the important characteristics of human speech. In voice conversion, we change the speaker identity from one to another, while keeping the linguistic cont…
Perception of prosodic variation for speech synthesis using an unsupervised discrete representation of F0
Zack Hodari, Catherine Lai, Simon King
In English, prosody adds a broad range of information to segment sequences, from information structure (e.g. contrast) to stylistic variation (e.g. expression of emotion). However,…
Comparison of Speech Representations for Automatic Quality Estimation in Multi-Speaker Text-to-Speech Synthesis
Jennifer Williams, Joanna Rownicka, Pilar Oplustil +1
We aim to characterize how different speakers contribute to the perceived output quality of multi-speaker Text-to-Speech (TTS) synthesis. We automatically rate the quality of TTS u…