User profiles for Taras Kucherenko
Taras KucherenkoLead ML Research Scientist at KB-Lab in the National Library of Sweden Verified email at kb.se Cited by 1962 |
Analyzing input and output representations for speech-driven gesture generation
This paper presents a novel framework for automatic speech-driven gesture generation,
applicable to human-agent interaction including both virtual agents and robots. Specifically, we …
applicable to human-agent interaction including both virtual agents and robots. Specifically, we …
Gesticulator: A framework for semantically-aware speech-driven gesture generation
T Kucherenko, P Jonell, S Van Waveren… - Proceedings of the …, 2020 - dl.acm.org
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 …
information. Similarly, realistic co-speech gestures are crucial to enable natural and smooth …
The GENEA Challenge 2023: A large-scale evaluation of gesture generation models in monadic and dyadic settings
This paper reports on the GENEA Challenge 2023, in which participating teams built speech-driven
gesture-generation systems using the same speech and motion dataset, followed by …
gesture-generation systems using the same speech and motion dataset, followed by …
A comprehensive review of data‐driven co‐speech gesture generation
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‐…
human communication. The automatic generation of such co‐speech gestures is a long‐…
Style‐controllable speech‐driven gesture synthesis using normalising flows
…, GE Henter, T Kucherenko… - Computer graphics …, 2020 - Wiley Online Library
Automatic synthesis of realistic gestures promises to transform the fields of animation, avatars
and communicative agents. In off‐line applications, novel tools can alter the role of an …
and communicative agents. In off‐line applications, novel tools can alter the role of an …
The GENEA Challenge 2022: A large evaluation of data-driven co-speech gesture generation
This paper reports on the second GENEA Challenge to benchmark data-driven automatic co-speech
gesture generation. Participating teams used the same speech and motion dataset …
gesture generation. Participating teams used the same speech and motion dataset …
A large, crowdsourced evaluation of gesture generation systems on common data: The GENEA Challenge 2020
Co-speech gestures, gestures that accompany speech, play an important role in human
communication. Automatic co-speech gesture generation is thus a key enabling technology for …
communication. Automatic co-speech gesture generation is thus a key enabling technology for …
Evaluating gesture generation in a large-scale open challenge: The GENEA Challenge 2022
This article reports on the second GENEA Challenge to benchmark data-driven automatic co-speech
gesture generation. Participating teams used the same speech and motion dataset …
gesture generation. Participating teams used the same speech and motion dataset …
Let's face it: Probabilistic multi-modal interlocutor-aware generation of facial gestures in dyadic settings
P Jonell, T Kucherenko, GE Henter… - Proceedings of the 20th …, 2020 - dl.acm.org
To enable more natural face-to-face interactions, conversational agents need to adapt their
behavior to their interlocutors. One key aspect of this is generation of appropriate non-verbal …
behavior to their interlocutors. One key aspect of this is generation of appropriate non-verbal …
Speech2properties2gestures: Gesture-property prediction as a tool for generating representational gestures from speech
We propose a new framework for gesture generation, aiming to allow data-driven approaches
to produce more semantically rich gestures. Our approach first predicts whether to gesture…
to produce more semantically rich gestures. Our approach first predicts whether to gesture…