# EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face Animation

arXiv: https://arxiv.org/abs/2303.11089 · HTML: https://mlsanity.com/paper/2303.11089/

## Key facts

- Cited by 142 papers in the map (data through 14 Oct 2026).
- Builds on 30 of its 63 references that are in the map.
- First posted on arXiv 20 Mar 2023.

## Builds on (most cited first, 30 of 30)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations](https://mlsanity.com/paper/2006.11477/) (2020)
- [Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation](https://mlsanity.com/paper/2108.12409/) (2021)
- [AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis](https://mlsanity.com/paper/2103.11078/) (2021)
- [Few-Shot Adversarial Learning of Realistic Neural Talking Head Models](https://mlsanity.com/paper/1905.08233/) (2019)
- [Capture, Learning, and Synthesis of 3D Speaking Styles](https://mlsanity.com/paper/1905.03079/) (2019)
- [Hierarchical Cross-Modal Talking Face Generationwith Dynamic Pixel-Wise Loss](https://mlsanity.com/paper/1905.03820/) (2019)
- [Neural Voice Puppetry: Audio-driven Facial Reenactment](https://mlsanity.com/paper/1912.05566/) (2019)
- [FaceFormer: Speech-Driven 3D Facial Animation with Transformers](https://mlsanity.com/paper/2112.05329/) (2021)
- [Temporal Convolutional Networks: A Unified Approach to Action Segmentation](https://mlsanity.com/paper/1608.08242/) (2016)
- [MeshTalk: 3D Face Animation from Speech using Cross-Modality Disentanglement](https://mlsanity.com/paper/2104.08223/) (2021)
- [Audio-Driven Emotional Video Portraits](https://mlsanity.com/paper/2104.07452/) (2021)
- [Depth-Aware Generative Adversarial Network for Talking Head Video Generation](https://mlsanity.com/paper/2203.06605/) (2022)
- [FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning](https://mlsanity.com/paper/2108.07938/) (2021)
- [MSP-Former: Multi-Scale Projection Transformer for Single Image Desnowing](https://mlsanity.com/paper/2207.05621/) (2022)
- [Modality Dropout for Improved Performance-driven Talking Faces](https://mlsanity.com/paper/2005.13616/) (2020)
- [Deep Learning on Monocular Object Pose Detection and Tracking: A Comprehensive Overview](https://mlsanity.com/paper/2105.14291/) (2021)
- [Object Level Depth Reconstruction for Category Level 6D Object Pose Estimation From Monocular RGB Image](https://mlsanity.com/paper/2204.01586/) (2022)
- [Neural Emotion Director: Speech-preserving semantic control of facial expressions in "in-the-wild" videos](https://mlsanity.com/paper/2112.00585/) (2021)
- [Animating Face using Disentangled Audio Representations](https://mlsanity.com/paper/1910.00726/) (2019)
- [Deep Learning for Visual Speech Analysis: A Survey](https://mlsanity.com/paper/2205.10839/) (2022)
- [Geometry-guided Dense Perspective Network for Speech-Driven Facial Animation](https://mlsanity.com/paper/2008.10004/) (2020)
- [VAW-GAN for Disentanglement and Recomposition of Emotional Elements in Speech](https://mlsanity.com/paper/2011.02314/) (2020)
- [iEmoTTS: Toward Robust Cross-Speaker Emotion Transfer and Control for Speech Synthesis based on Disentanglement between Prosody and Timbre](https://mlsanity.com/paper/2206.14866/) (2022)
- [Continuously Controllable Facial Expression Editing in Talking Face Videos](https://mlsanity.com/paper/2209.08289/) (2022)
- [Transformer-S2A: Robust and Efficient Speech-to-Animation](https://mlsanity.com/paper/2111.09771/) (2021)
- [Audio2Face: Generating Speech/Face Animation from Single Audio with Attention-Based Bidirectional LSTM Networks](https://mlsanity.com/paper/1905.11142/) (2019)
- [Reconstruction-Aware Prior Distillation for Semi-supervised Point Cloud Completion](https://mlsanity.com/paper/2204.09186/) (2022)

## Built on by (most cited first, 30 of 142)

- [EMAGE: Towards Unified Holistic Co-Speech Gesture Generation via Expressive Masked Audio Gesture Modeling](https://mlsanity.com/paper/2401.00374/) (2023)
- [Emotional Speech-Driven Animation with Content-Emotion Disentanglement](https://mlsanity.com/paper/2306.08990/) (2023)
- [SyncTalk: The Devil is in the Synchronization for Talking Head Synthesis](https://mlsanity.com/paper/2311.17590/) (2023)
- [DiffPoseTalk: Speech-Driven Stylistic 3D Facial Animation and Head Pose Generation via Diffusion Models](https://mlsanity.com/paper/2310.00434/) (2023)
- [SelfTalk: A Self-Supervised Commutative Training Diagram to Comprehend 3D Talking Faces](https://mlsanity.com/paper/2306.10799/) (2023)
- [Deepfake Generation and Detection: A Benchmark and Survey](https://mlsanity.com/paper/2403.17881/) (2024)
- [AniTalker: Animate Vivid and Diverse Talking Faces through Identity-Decoupled Facial Motion Encoding](https://mlsanity.com/paper/2405.03121/) (2024)
- [FaceTalk: Audio-Driven Motion Diffusion for Neural Parametric Head Models](https://mlsanity.com/paper/2312.08459/) (2023)
- [Emotional Speech-driven 3D Body Animation via Disentangled Latent Diffusion](https://mlsanity.com/paper/2312.04466/) (2023)
- [Media2Face: Co-speech Facial Animation Generation With Multi-Modality Guidance](https://mlsanity.com/paper/2401.15687/) (2024)
- [FlowVQTalker: High-Quality Emotional Talking Face Generation through Normalizing Flow and Quantization](https://mlsanity.com/paper/2403.06375/) (2024)
- [DualTalk: Dual-Speaker Interaction for 3D Talking Head Conversations](https://mlsanity.com/paper/2505.18096/) (2025)
- [UniTalker: Scaling up Audio-Driven 3D Facial Animation through A Unified Model](https://mlsanity.com/paper/2408.00762/) (2024)
- [ARTalk: Speech-Driven 3D Head Animation via Autoregressive Model](https://mlsanity.com/paper/2502.20323/) (2025)
- [MultiTalk: Enhancing 3D Talking Head Generation Across Languages with Multilingual Video Dataset](https://mlsanity.com/paper/2406.14272/) (2024)
- [LaughTalk: Expressive 3D Talking Head Generation with Laughter](https://mlsanity.com/paper/2311.00994/) (2023)
- [OmniSync: Towards Universal Lip Synchronization via Diffusion Transformers](https://mlsanity.com/paper/2505.21448/) (2025)
- [DREAM-Talk: Diffusion-based Realistic Emotional Audio-driven Method for Single Image Talking Face Generation](https://mlsanity.com/paper/2312.13578/) (2023)
- [ScanTalk: 3D Talking Heads from Unregistered Scans](https://mlsanity.com/paper/2403.10942/) (2024)
- [FaceChain-ImagineID: Freely Crafting High-Fidelity Diverse Talking Faces from Disentangled Audio](https://mlsanity.com/paper/2403.01901/) (2024)
- [Speech-Driven 3D Face Animation with Composite and Regional Facial Movements](https://mlsanity.com/paper/2308.05428/) (2023)
- [DiffusionTalker: Personalization and Acceleration for Speech-Driven 3D Face Diffuser](https://mlsanity.com/paper/2311.16565/) (2023)
- [DreamTalk: When Emotional Talking Head Generation Meets Diffusion Probabilistic Models](https://mlsanity.com/paper/2312.09767/) (2023)
- [Mimic: Speaking Style Disentanglement for Speech-Driven 3D Facial Animation](https://mlsanity.com/paper/2312.10877/) (2023)
- [Learn2Talk: 3D Talking Face Learns from 2D Talking Face](https://mlsanity.com/paper/2404.12888/) (2024)
- [MMHead: Towards Fine-grained Multi-modal 3D Facial Animation](https://mlsanity.com/paper/2410.07757/) (2024)
- [MagicInfinite: Generating Infinite Talking Videos with Your Words and Voice](https://mlsanity.com/paper/2503.05978/) (2025)
- [3DiFACE: Diffusion-based Speech-driven 3D Facial Animation and Editing](https://mlsanity.com/paper/2312.00870/) (2023)
- [SkyReels-Audio: Omni Audio-Conditioned Talking Portraits in Video Diffusion Transformers](https://mlsanity.com/paper/2506.00830/) (2025)
- [EmoVOCA: Speech-Driven Emotional 3D Talking Heads](https://mlsanity.com/paper/2403.12886/) (2024)

## Abstract (arXiv)

Speech-driven 3D face animation aims to generate realistic facial expressions that match the speech content and emotion. However, existing methods often neglect emotional facial expressions or fail to disentangle them from speech content. To address this issue, this paper proposes an end-to-end neural network to disentangle different emotions in speech so as to generate rich 3D facial expressions. Specifically, we introduce the emotion disentangling encoder (EDE) to disentangle the emotion and content in the speech by cross-reconstructed speech signals with different emotion labels. Then an emotion-guided feature fusion decoder is employed to generate a 3D talking face with enhanced emotion. The decoder is driven by the disentangled identity, emotional, and content embeddings so as to generate controllable personal and emotional styles. Finally, considering the scarcity of the 3D emotional talking face data, we resort to the supervision of facial blendshapes, which enables the reconstruction of plausible 3D faces from 2D emotional data, and contribute a large-scale 3D emotional talking face dataset (3D-ETF) to train the network. Our experiments and user studies demonstrate that our approach outperforms state-of-the-art methods and exhibits more diverse facial movements. We recommend watching the supplementary video: https://ziqiaopeng.github.io/emotalk