Speech2Properties2Gestures: Gesture-Property Prediction as a Tool for Generating Representational Gestures from Speech
Taras Kucherenko, Rajmund Nagy, Patrik Jonell, Michael Neff, Hedvig Kjellström, Gustav Eje Henter
[Project proposal (IVA'21 Honorable Mention)]
[Analysis of gesture property predictability (AAMAS'22)]
[SaGA++ Dataset]
[Code]
ABSTRACT
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, followed by a prediction of the gesture properties. Those properties are then used as conditioning for a modern probabilistic gesture-generation model capable of high-quality output. This empowers the approach to generate gestures that are both diverse and representational.
Citation format for the general idea:
@inproceedings{kucherenko2021speech2properties2gestures,
title={Speech2{P}roperties2{G}estures: {G}esture-Property Prediction as a Tool for Generating Representational Gestures from Speech},
author={Kucherenko, Taras and Nagy, Rajmund and Jonell, Patrik and Neff, Michael and Kjellstr{\"o}m, Hedvig and Henter, Gustav Eje},
year={2021},
isbn = {9781450366724},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3472306.347833},
doi = {10.1145/3472306.347833},
booktitle = {Proceedings of the 21th ACM International Conference on Intelligent Virtual Agents},
location = {Virtual Event, Japan},
series = {IVA '21}
}
Citation format for the gesture property predictibility analysis:
@inproceedings{kucherenko2022multimodal,
title={Multimodal analysis of the predictability of hand-gesture properties},
author={Kucherenko, Taras and Nagy, Rajmund and Neff, Michael and Kjellstr{\"o}m, Hedvig and Henter, Gustav Eje},
booktitle = {Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems},
series = {AAMAS '22}
year={2022}
}