# A large, crowdsourced evaluation of gesture generation systems on common data: The GENEA Challenge 2020

arXiv: https://arxiv.org/abs/2102.11617 · HTML: https://mlsanity.com/paper/2102.11617/

## Key facts

- Cited by 38 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Feb 2021.

## Built on by (most cited first, 30 of 38)

- [Listen, Denoise, Action! Audio-Driven Motion Synthesis with Diffusion Models](https://mlsanity.com/paper/2211.09707/) (2022)
- [Human Motion Generation: A Survey](https://mlsanity.com/paper/2307.10894/) (2023)
- [DiffuseStyleGesture: Stylized Audio-Driven Co-Speech Gesture Generation with Diffusion Models](https://mlsanity.com/paper/2305.04919/) (2023)
- [ZeroEGGS: Zero-shot Example-based Gesture Generation from Speech](https://mlsanity.com/paper/2209.07556/) (2022)
- [A Comprehensive Review of Data-Driven Co-Speech Gesture Generation](https://mlsanity.com/paper/2301.05339/) (2023)
- [Speech2AffectiveGestures: Synthesizing Co-Speech Gestures with Generative Adversarial Affective Expression Learning](https://mlsanity.com/paper/2108.00262/) (2021)
- [MambaTalk: Efficient Holistic Gesture Synthesis with Selective State Space Models](https://mlsanity.com/paper/2403.09471/) (2024)
- [The GENEA Challenge 2022: A large evaluation of data-driven co-speech gesture generation](https://mlsanity.com/paper/2208.10441/) (2022)
- [QPGesture: Quantization-Based and Phase-Guided Motion Matching for Natural Speech-Driven Gesture Generation](https://mlsanity.com/paper/2305.11094/) (2023)
- [Rhythmic Gesticulator: Rhythm-Aware Co-Speech Gesture Synthesis with Hierarchical Neural Embeddings](https://mlsanity.com/paper/2210.01448/) (2022)
- [Co-Speech Gesture Video Generation via Motion-Decoupled Diffusion Model](https://mlsanity.com/paper/2404.01862/) (2024)
- [SemTalk: Holistic Co-speech Motion Generation with Frame-level Semantic Emphasis](https://mlsanity.com/paper/2412.16563/) (2024)
- [Evaluating gesture generation in a large-scale open challenge: The GENEA Challenge 2022](https://mlsanity.com/paper/2303.08737/) (2023)
- [The GENEA Challenge 2023: A large scale evaluation of gesture generation models in monadic and dyadic settings](https://mlsanity.com/paper/2308.12646/) (2023)
- [Transflower: probabilistic autoregressive dance generation with multimodal attention](https://mlsanity.com/paper/2106.13871/) (2021)
- [DiffMotion: Speech-Driven Gesture Synthesis Using Denoising Diffusion Model](https://mlsanity.com/paper/2301.10047/) (2023)
- [BodyFormer: Semantics-guided 3D Body Gesture Synthesis with Transformer](https://mlsanity.com/paper/2310.06851/) (2023)
- [What is the Best Automated Metric for Text to Motion Generation?](https://mlsanity.com/paper/2309.10248/) (2023)
- [Integrated Speech and Gesture Synthesis](https://mlsanity.com/paper/2108.11436/) (2021)
- [UnifiedGesture: A Unified Gesture Synthesis Model for Multiple Skeletons](https://mlsanity.com/paper/2309.07051/) (2023)
- [Multimodal analysis of the predictability of hand-gesture properties](https://mlsanity.com/paper/2108.05762/) (2021)
- [Diff-TTSG: Denoising probabilistic integrated speech and gesture synthesis](https://mlsanity.com/paper/2306.09417/) (2023)
- [Speech2Properties2Gestures: Gesture-Property Prediction as a Tool for Generating Representational Gestures from Speech](https://mlsanity.com/paper/2106.14736/) (2021)
- [Didn't see that coming: a survey on non-verbal social human behavior forecasting](https://mlsanity.com/paper/2203.02480/) (2022)
- [Audio2Gestures: Generating Diverse Gestures from Audio](https://mlsanity.com/paper/2301.06690/) (2023)
- [The ReprGesture entry to the GENEA Challenge 2022](https://mlsanity.com/paper/2208.12133/) (2022)
- [Co-Speech Gesture Synthesis using Discrete Gesture Token Learning](https://mlsanity.com/paper/2303.12822/) (2023)
- [PersonaGesture: Single-Reference Co-Speech Gesture Personalization for Unseen Speakers](https://mlsanity.com/paper/2605.06064/) (2026)
- [Unified speech and gesture synthesis using flow matching](https://mlsanity.com/paper/2310.05181/) (2023)
- [MMoFusion: Multi-modal Co-Speech Motion Generation with Diffusion Model](https://mlsanity.com/paper/2403.02905/) (2024)

## Abstract (arXiv)

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 embodied conversational agents (ECAs), since humans expect ECAs to be capable of multi-modal communication. Research into gesture generation is rapidly gravitating towards data-driven methods. Unfortunately, individual research efforts in the field are difficult to compare: there are no established benchmarks, and each study tends to use its own dataset, motion visualisation, and evaluation methodology. To address this situation, we launched the GENEA Challenge, a gesture-generation challenge wherein participating teams built automatic gesture-generation systems on a common dataset, and the resulting systems were evaluated in parallel in a large, crowdsourced user study using the same motion-rendering pipeline. Since differences in evaluation outcomes between systems now are solely attributable to differences between the motion-generation methods, this enables benchmarking recent approaches against one another in order to get a better impression of the state of the art in the field. This paper reports on the purpose, design, results, and implications of our challenge.