23 citations · 37 across the 7 of their papers we have counts for
5 papers · 1 filter
Should you use a probabilistic duration model in TTS? Probably! Especially for spontaneous speech
Shivam Mehta, Harm Lameris, Rajiv Punmiya +3
Converting input symbols to output audio in TTS requires modelling the durations of speech sounds. Leading non-autoregressive (NAR) TTS models treat duration modelling as a regress…
Unified speech and gesture synthesis using flow matching
Shivam Mehta, Ruibo Tu, Simon Alexanderson +3
As text-to-speech technologies achieve remarkable naturalness in read-aloud tasks, there is growing interest in multimodal synthesis of verbal and non-verbal communicative behaviou…
Diffusion-Based Co-Speech Gesture Generation Using Joint Text and Audio Representation
Anna Deichler, Shivam Mehta, Simon Alexanderson +1
This paper describes a system developed for the GENEA (Generation and Evaluation of Non-verbal Behaviour for Embodied Agents) Challenge 2023. Our solution builds on an existing dif…
Matcha-TTS: A fast TTS architecture with conditional flow matching
Shivam Mehta, Ruibo Tu, Jonas Beskow +2
We introduce Matcha-TTS, a new encoder-decoder architecture for speedy TTS acoustic modelling, trained using optimal-transport conditional flow matching (OT-CFM). This yields an OD…
Diff-TTSG: Denoising probabilistic integrated speech and gesture synthesis
Shivam Mehta, Siyang Wang, Simon Alexanderson +3
With read-aloud speech synthesis achieving high naturalness scores, there is a growing research interest in synthesising spontaneous speech. However, human spontaneous face-to-face…