19 citations · 35 across the 3 of their papers we have counts for
5 papers
Integrated Speech and Gesture Synthesis
Siyang Wang, Simon Alexanderson, Joakim Gustafson +3
Text-to-speech and co-speech gesture synthesis have until now been treated as separate areas by two different research communities, and applications merely stack the two technologi…
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…
Robust model training and generalisation with Studentising flows
Simon Alexanderson, Gustav Eje Henter
Normalising flows are tractable probabilistic models that leverage the power of deep learning to describe a wide parametric family of distributions, all while remaining trainable u…
Gesticulator: A framework for semantically-aware speech-driven gesture generation
Taras Kucherenko, Patrik Jonell, Sanne van Waveren +4
During speech, people spontaneously gesticulate, which plays a key role in conveying information. Similarly, realistic co-speech gestures are crucial to enable natural and smooth i…
MoGlow: Probabilistic and controllable motion synthesis using normalising flows
Gustav Eje Henter, Simon Alexanderson, Jonas Beskow
Data-driven modelling and synthesis of motion is an active research area with applications that include animation, games, and social robotics. This paper introduces a new class of…