| --- |
| license: cc-by-nc-4.0 |
| task_categories: |
| - audio-classification |
| - video-text-to-text |
| - question-answering |
| language: |
| - en |
| size_categories: |
| - 1K<n<10K |
| tags: |
| - benchmark |
| - evaluation |
| - audio-visual |
| - synchronization |
| - vggsound |
| - multimodal |
| - mllm |
| pretty_name: "VGGSync-3K: out-of-domain audio-visual sync benchmark" |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: eval/test_3k.jsonl |
| --- |
| |
| # VGGSync-3K · out-of-domain audio-visual sync benchmark |
|
|
| Out-of-domain evaluation set used in the paper |
| **[When Vision Speaks for Sound](https://arxiv.org/abs/2605.16403)**. |
|
|
| Derived from [VGGSoundSync](https://www.robots.ox.ac.uk/~vgg/research/avs/), |
| this 3,000-clip slice tests whether a video-capable MLLM can detect |
| audio temporal offsets on **everyday sound events** outside the THUD |
| in-domain training distribution. |
|
|
| Each item is one VGGSound clip in one of three conditions: |
|
|
| | Condition | Count | `gt_synced` | `gt_direction` | `gt_offset_sec` | |
| |---|---:|---|---|---| |
| | Audio aligned (no shift) | 1,000 | `true` | `none` | `0.0` | |
| | Audio shifted **early** | 1,000 | `false` | `early` | shift amount | |
| | Audio shifted **delay** | 1,000 | `false` | `delay` | shift amount | |
|
|
| Shift magnitudes span 4 difficulty levels (`very_easy`, `easy`, `medium`, |
| `hard`); synced clips are tagged `difficulty=synced`. |
|
|
| ## What's in this repo |
|
|
| | File | Description | |
| |---|---| |
| | `eval/test_3k.jsonl` | Test records — uid / label / paths / ground truth | |
| | `media.zip` | All referenced videos + audios | |
|
|
| ## How to use |
|
|
| ```bash |
| # Download |
| hf download Rakancorle1/vggsync-3k --repo-type=dataset --local-dir vggsync-3k |
| cd vggsync-3k |
| |
| # Unzip media — paths in JSONL resolve automatically |
| unzip -q media.zip |
| ``` |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("Rakancorle1/vggsync-3k") |
| ``` |
|
|
| ## Record schema |
|
|
| ```jsonc |
| { |
| "uid": "-r3nM90RCNs_medium_early_0.5s", |
| "ytid": "-r3nM90RCNs", |
| "label": "sharpen knife", |
| "difficulty": "very_easy" | "easy" | "medium" | "hard" | "synced", |
| "video_path": "videos/<uid>.mp4", |
| "audio_path": "audios/<uid>.wav", |
| "gt_synced": true | false, |
| "gt_direction": "none" | "early" | "delay", |
| "gt_offset_sec": 0.0 // > 0 for shifted; sign implied by direction |
| } |
| ``` |
|
|
| `uid` follows the pattern `<ytid>_<difficulty>_<direction>_<offset>s` |
| for shifted clips, and `<ytid>` alone for synced clips. |
|
|
| ## Reference eval scripts |
|
|
| Paper evaluation code lives in the |
| [wvs-code repository](https://github.com/rakanWen/wvs-code) on GitHub. |
|
|
| The JSONL is self-contained — `video_path`, `audio_path`, and the `gt_*` |
| fields are all you need to compare any model's output against ground truth. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{wen2026whenvisionspeaksforsound, |
| title = {When Vision Speaks for Sound}, |
| author = {Xiaofei Wen and Wenjie Jacky Mo and Xingyu Fu and Rui Cai and |
| Tinghui Zhu and Wendi Li and Yanan Xie and Muhao Chen and Peng Qi}, |
| year = {2026}, |
| url = {https://arxiv.org/abs/2605.16403} |
| } |
| ``` |
|
|
| Please also cite the original VGGSoundSync work: |
|
|
| ```bibtex |
| @InProceedings{Chen21b, |
| title = "Audio-Visual Synchronization in the Wild", |
| author = "Honglie Chen, Weidi Xie, Triantafyllos Afouras, Arsha Nagrani, Andrea Vedaldi, Andrew Zisserman", |
| booktitle = "BMVC", |
| year = "2021"} |
| ``` |
|
|
| ## Related releases |
|
|
| - **[Rakancorle1/thud-eval](https://huggingface.co/datasets/Rakancorle1/thud-eval)** — in-domain audio-visual Clever Hans benchmark (sync / mute / swap) |
| - **[Rakancorle1/hans-10k](https://huggingface.co/datasets/Rakancorle1/hans-10k)** — DPO training data |
| - **[Rakancorle1/hans-sft-4k](https://huggingface.co/datasets/Rakancorle1/hans-sft-4k)** — SFT training data |
| - **[Collection](https://huggingface.co/collections/Rakancorle1/when-vision-speaks-for-sound)** — everything in one place |
|
|
| ## License |
|
|
| This subset is released under **CC-BY-NC-4.0** for the annotations and |
| shifted-clip pairings. The underlying audio/video content is derived |
| from VGGSound — please follow VGGSound's licensing terms when using or |
| redistributing. |
|
|
