| --- |
| pretty_name: WebTalk-Synthetic |
| license: cc-by-nc-4.0 |
| language: |
| - en |
| task_categories: |
| - audio-to-audio |
| - other |
| tags: |
| - co-speech |
| - facial-animation |
| - talking-face |
| - FLAME |
| - synthetic |
| - 3d-motion |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # WebTalk-Synthetic |
|
|
| **WebTalk-Synthetic** is a dataset of **synthetic in-the-wild co-speech facial |
| motion**: ~12.7 k short clips, each pairing conversational speech with a |
| *generated* 3D facial-motion track in [FLAME](https://flame.is.tue.mpg.de/) |
| coefficient space. The facial motion is produced by an audio-driven face model |
| from filtered in-the-wild talking audio — it is synthesized, not |
| motion-captured. The dataset was created for and used by |
| [ViBES](https://github.com/Juzezhang/ViBES) (CVPR 2026) to give the face expert |
| broad in-the-wild coverage. |
|
|
| > ⚠️ **Research use only.** The audio is segmented from public talking-head |
| > videos. This dataset is released under **CC-BY-NC-4.0 for non-commercial |
| > research only**. Do not use it for commercial purposes. |
|
|
| ## Download |
|
|
| ```bash |
| huggingface-cli download JuzeZhang/WebTalk-Synthetic \ |
| --repo-type dataset --local-dir WebTalk-Synthetic |
| ``` |
|
|
| Each modality is shipped as a single `.tar` (far faster to upload/sync than ~50k |
| loose files). Extract them in place after download: |
|
|
| ```bash |
| cd WebTalk-Synthetic |
| for f in audios audios_token_glm FLAME_coeffs_25 transcripts; do tar -xf "$f.tar"; done |
| # optionally: rm *.tar |
| ``` |
|
|
| ## Dataset structure |
|
|
| In the repo (as shipped): |
|
|
| ``` |
| WebTalk-Synthetic/ |
| ├── audios.tar → audios/ (16 kHz mono WAV, one per clip) |
| ├── audios_token_glm.tar → audios_token_glm/ (GLM-4-Voice audio tokens, one .npy per clip) |
| ├── FLAME_coeffs_25.tar → FLAME_coeffs_25/ (synthetic FLAME face motion, one .npz, 25 fps) |
| ├── transcripts.tar → transcripts/ (one .txt per clip) |
| ├── train.txt (12,075 clip stems) |
| ├── val.txt (290 clip stems) |
| ├── test.txt (304 clip stems) |
| ├── README.md |
| └── LICENSE |
| ``` |
|
|
| `audios_token_glm/<stem>.npy` is a `(N,) int64` array of |
| [GLM-4-Voice](https://github.com/THUDM/GLM-4-Voice) discrete audio tokens, |
| provided so you can skip re-running audio tokenization. |
|
|
| Every modality is keyed by a clip stem of the form `<session>_<segment>` |
| (e.g. `202008647_0001`); `audios/<stem>.wav`, `FLAME_coeffs_25/<stem>.npz`, and |
| `transcripts/<stem>.txt` all refer to the same clip. |
|
|
| - **12,669 clips total** (12,075 train / 290 val / 304 test). |
|
|
| ### FLAME motion format (`FLAME_coeffs_25/<stem>.npz`) |
|
|
| | Key | Shape | dtype | Description | |
| |---|---|---|---| |
| | `exp` | `(T, 100)` | float32 | FLAME expression coefficients | |
| | `shape` | `(T, 100)` | float64 | FLAME shape coefficients | |
| | `pose` | `(T, 6)` | float32 | head pose (3) + jaw pose (3), axis-angle | |
| | `mocap_frame_rate` | scalar | int64 | 25 | |
|
|
| `T` is the per-clip frame count at 25 fps. |
|
|
| ### Audio |
|
|
| 16 kHz mono PCM WAV, ~8 s per clip. |
|
|
| ## Usage |
|
|
| Load a clip directly: |
|
|
| ```python |
| import numpy as np, soundfile as sf |
| |
| stem = "202008647_0001" |
| audio, sr = sf.read(f"audios/{stem}.wav") # 16 kHz mono |
| coef = np.load(f"FLAME_coeffs_25/{stem}.npz") # exp / shape / pose |
| text = open(f"transcripts/{stem}.txt").read() |
| ``` |
|
|
| The full ViBES preprocessing recipe (audio tokenization, face VQ-VAE |
| tokenization, and building the training-ready HuggingFace dataset) is documented |
| in [`docs/1-data/webtalk_synthetic.md`](https://github.com/Juzezhang/ViBES/blob/main/docs/1-data/webtalk_synthetic.md). |
|
|
| ## Intended use & limitations |
|
|
| - Intended for **non-commercial research** on co-speech facial animation, |
| audio-driven face generation, and conversational virtual humans. |
| - The facial motion is **model-generated**, not ground-truth capture; it reflects |
| the biases and failure modes of the audio-driven face model that produced it. |
| - Audio originates from public talking-head videos; treat it accordingly and do |
| not attempt to re-identify speakers. |
|
|
| ## License |
|
|
| [CC-BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/) — non-commercial |
| research use only. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{zhang2026vibes, |
| title={ViBES: A Conversational Agent with Behaviorally-Intelligent 3D Virtual Body}, |
| author={Juze Zhang and Changan Chen and Xin Chen and Heng Yu and Tiange Xiang and Ali Sartaz Khan and Shrinidhi Kowshika Lakshmikanth and Ehsan Adeli}, |
| booktitle={CVPR}, |
| year={2026}, |
| } |
| ``` |
|
|
