Gestures that accompany speech are an essential part of natural and efficient embodied
human communication. The automatic generation of such co‐speech gestures is a long …

Diffusion models have experienced a surge of interest as highly expressive yet efficiently
trainable probabilistic models. We show that these models are an excellent fit for …

Achieving realistic, vivid, and human-like synthesized conversational gestures conditioned
on multi-modal data is still an unsolved problem due to the lack of available datasets …

Speech-driven gesture generation is highly challenging due to the random jitters of human
motion. In addition, there is an inherent asynchronous relationship between human speech …

This paper describes the IVI Lab entry to the GENEA Challenge 2022. We formulate the
gesture generation problem as a sequence-to-sequence conversion task with text, audio …

With read-aloud speech synthesis achieving high naturalness scores, there is a growing
research interest in synthesising spontaneous speech. However, human spontaneous face …

The automatic co-speech gesture generation draws much attention in computer animation.
Previous works designed network structures on individual datasets, which resulted in a lack …

Research on creation of virtual humans enables increasing automatization of their behavior,
including synthesis of verbal and nonverbal behavior. As the achievable realism of different …

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 …

Most manual communicative gestures that humans produce cannot be looked up in a
dictionary, as these manual gestures inherit their meaning in large part from the …