19 citations · 53 across the 7 of their papers we have counts for
7 papers
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…
On the Use of Self-Supervised Speech Representations in Spontaneous Speech Synthesis
Siyang Wang, Gustav Eje Henter, Joakim Gustafson +1
Self-supervised learning (SSL) speech representations learned from large amounts of diverse, mixed-quality speech data without transcriptions are gaining ground in many speech tech…
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…
Automatic Evaluation of Turn-taking Cues in Conversational Speech Synthesis
Erik Ekstedt, Siyang Wang, Éva Székely +2
Turn-taking is a fundamental aspect of human communication where speakers convey their intention to either hold, or yield, their turn through prosodic cues. Using the recently prop…
OverFlow: Putting flows on top of neural transducers for better TTS
Shivam Mehta, Ambika Kirkland, Harm Lameris +3
Neural HMMs are a type of neural transducer recently proposed for sequence-to-sequence modelling in text-to-speech. They combine the best features of classic statistical speech syn…
Neural HMMs are all you need (for high-quality attention-free TTS)
Shivam Mehta, Éva Székely, Jonas Beskow +1
Neural sequence-to-sequence TTS has achieved significantly better output quality than statistical speech synthesis using HMMs. However, neural TTS is generally not probabilistic an…
Generating coherent spontaneous speech and gesture from text
Simon Alexanderson, Éva Székely, Gustav Eje Henter +2
Embodied human communication encompasses both verbal (speech) and non-verbal information (e.g., gesture and head movements). Recent advances in machine learning have substantially…