GENEA Challenge 2022 objective evaluation data

This Zenodo repository contains objective evaluation results for all test-set motion submitted by teams participating in the GENEA Challenge 2022.

We caution the user that objective metrics are known to have poor correlation with actual, perceived motion quality. For definitions and explanations of the "Average jerk magnitude", "Average acceleration magnitude", and "Average Hellinger distance", please see the paper "Moving fast and slow: Analysis of representations and post-processing in speech-driven automatic gesture generation" by Kucherenko et al., published in the International Journal of Human–Computer Interaction in 2021. For a definition and explanation of the "Canonical correlation analysis (CCA) coefficient", see the paper "Speech-driven animation with meaningful behaviors" by Sadoughi and Busso, published in Speech Communication in 2019. Code for computing these objective metrics is available through the challenge webpage.

Attribution:

If you use this material, please cite our latest paper on the GENEA Challenge 2022. At the time of writing (2022-08-10) this is our ACM ICMI 2022 paper:

Youngwoo Yoon, Pieter Wolfert, Taras Kucherenko, Carla Viegas, Teodor Nikolov, Mihail Tsakov, and Gustav Eje Henter. 2022. The GENEA Challenge 2022: A large evaluation of data-driven co-speech gesture generation. In Proceedings of the ACM International Conference on Multimodal Interaction (ICMI '22). ACM.

You can find the latest information and a BibTeX file on the project website:

https://youngwoo-yoon.github.io/GENEAchallenge2022/

The material is available under a CC BY 4.0 international license, with the text provided in LICENSE.txt.

To find more GENEA Challenge 2022 material on the web, please see:

* https://youngwoo-yoon.github.io/GENEAchallenge2022/

* https://genea-workshop.github.io/2022/challenge/

If you have any questions or comments, please contact:

* The GENEA Challenge & Workshop organisers