154 citations · 289 across the 8 of their papers we have counts for
14 papers
Evaluating Data-Driven Co-Speech Gestures of Embodied Conversational Agents through Real-Time Interaction
Yuan He, André Pereira, Taras Kucherenko
Embodied Conversational Agents that make use of co-speech gestures can enhance human-machine interactions in many ways. In recent years, data-driven gesture generation approaches f…
To Rate or Not To Rate: Investigating Evaluation Methods for Generated Co-Speech Gestures
Pieter Wolfert, Jeffrey M. Girard, Taras Kucherenko +1
While automatic performance metrics are crucial for machine learning of artificial human-like behaviour, the gold standard for evaluation remains human judgement. The subjective ev…
Speech2Properties2Gestures: Gesture-Property Prediction as a Tool for Generating Representational Gestures from Speech
Taras Kucherenko, Rajmund Nagy, Patrik Jonell +3
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…
A Framework for Integrating Gesture Generation Models into Interactive Conversational Agents
Rajmund Nagy, Taras Kucherenko, Birger Moell +3
Embodied conversational agents (ECAs) benefit from non-verbal behavior for natural and efficient interaction with users. Gesticulation - hand and arm movements accompanying speech…
A large, crowdsourced evaluation of gesture generation systems on common data: The GENEA Challenge 2020
Taras Kucherenko, Patrik Jonell, Youngwoo Yoon +2
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 embo…
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…