# Gesticulator: A framework for semantically-aware speech-driven gesture generation

arXiv: https://arxiv.org/abs/2001.09326 · HTML: https://mlsanity.com/paper/2001.09326/

## Key facts

- Cited by 84 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Jan 2020.

## Built on by (most cited first, 30 of 84)

- [Listen, Denoise, Action! Audio-Driven Motion Synthesis with Diffusion Models](https://mlsanity.com/paper/2211.09707/) (2022)
- [Generating Holistic 3D Human Motion from Speech](https://mlsanity.com/paper/2212.04420/) (2022)
- [BEAT: A Large-Scale Semantic and Emotional Multi-Modal Dataset for Conversational Gestures Synthesis](https://mlsanity.com/paper/2203.05297/) (2022)
- [GestureDiffuCLIP: Gesture Diffusion Model with CLIP Latents](https://mlsanity.com/paper/2303.14613/) (2023)
- [Learning Hierarchical Cross-Modal Association for Co-Speech Gesture Generation](https://mlsanity.com/paper/2203.13161/) (2022)
- [Learning Speech-driven 3D Conversational Gestures from Video](https://mlsanity.com/paper/2102.06837/) (2021)
- [Human Motion Generation: A Survey](https://mlsanity.com/paper/2307.10894/) (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)
- [DiffSHEG: A Diffusion-Based Approach for Real-Time Speech-driven Holistic 3D Expression and Gesture Generation](https://mlsanity.com/paper/2401.04747/) (2024)
- [Speech2AffectiveGestures: Synthesizing Co-Speech Gestures with Generative Adversarial Affective Expression Learning](https://mlsanity.com/paper/2108.00262/) (2021)
- [Audio-Driven Co-Speech Gesture Video Generation](https://mlsanity.com/paper/2212.02350/) (2022)
- [Learning in Audio-visual Context: A Review, Analysis, and New Perspective](https://mlsanity.com/paper/2208.09579/) (2022)
- [ConvoFusion: Multi-Modal Conversational Diffusion for Co-Speech Gesture Synthesis](https://mlsanity.com/paper/2403.17936/) (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)
- [Can Language Models Learn to Listen?](https://mlsanity.com/paper/2308.10897/) (2023)
- [Semantic Gesticulator: Semantics-Aware Co-Speech Gesture Synthesis](https://mlsanity.com/paper/2405.09814/) (2024)
- [Rhythmic Gesticulator: Rhythm-Aware Co-Speech Gesture Synthesis with Hierarchical Neural Embeddings](https://mlsanity.com/paper/2210.01448/) (2022)
- [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)
- [Diffusion-Based Co-Speech Gesture Generation Using Joint Text and Audio Representation](https://mlsanity.com/paper/2309.05455/) (2023)
- [BodyFormer: Semantics-guided 3D Body Gesture Synthesis with Transformer](https://mlsanity.com/paper/2310.06851/) (2023)
- [DiffTED: One-shot Audio-driven TED Talk Video Generation with Diffusion-based Co-speech Gestures](https://mlsanity.com/paper/2409.07649/) (2024)
- [Audio-driven Neural Gesture Reenactment with Video Motion Graphs](https://mlsanity.com/paper/2207.11524/) (2022)
- [SemGes: Semantics-aware Co-Speech Gesture Generation using Semantic Coherence and Relevance Learning](https://mlsanity.com/paper/2507.19359/) (2025)
- [Integrated Speech and Gesture Synthesis](https://mlsanity.com/paper/2108.11436/) (2021)
- [Multiple Appropriate Facial Reaction Generation in Dyadic Interaction Settings: What, Why and How?](https://mlsanity.com/paper/2302.06514/) (2023)
- [Joint Audio-Text Model for Expressive Speech-Driven 3D Facial Animation](https://mlsanity.com/paper/2112.02214/) (2021)

## Abstract (arXiv)

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 interactions with social agents. Current end-to-end co-speech gesture generation systems use a single modality for representing speech: either audio or text. These systems are therefore confined to producing either acoustically-linked beat gestures or semantically-linked gesticulation (e.g., raising a hand when saying "high"): they cannot appropriately learn to generate both gesture types. We present a model designed to produce arbitrary beat and semantic gestures together. Our deep-learning based model takes both acoustic and semantic representations of speech as input, and generates gestures as a sequence of joint angle rotations as output. The resulting gestures can be applied to both virtual agents and humanoid robots. Subjective and objective evaluations confirm the success of our approach. The code and video are available at the project page https://svito-zar.github.io/gesticulator .