| ---
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| license: apache-2.0
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| ---
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| # VidAudio-Bench: Benchmarking V2A and VT2A Generation across Five Audio Categories
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| ## 1. Overview
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| VidAudio-Bench is a comprehensive multi-task benchmark designed for evaluating both Video-to-Audio (V2A) and Video-Text-to-Audio (VT2A) generation systems.
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| The benchmark comprises 1,634 video-text pairs spanning five audio categories:
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| - SFX: 400 samples
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| - Music: Instrument: 191 samples ; BGM: 231 samples
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| - Speech: 412 samples
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| - Singing: 400 samples
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| VidAudio-Bench aims to facilitate the evaluation of:
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| - Audio-video synchronization
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| - Semantic consistency between video and generated audio
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| - Text-guided controllable audio generation
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| - Fine-grained audio category understanding
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| ---
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| ## 2. Dataset Structure
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| The dataset is organized as follows:
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| ```text
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| VidAudio-Bench/
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| ├── original_videos/ # original video files (.mp4)
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| ├── silent_videos/ # muted video files (.mp4)
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| ├── annotations/ # metadata files (.jsonl)
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| ```
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| ---
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| ## 3. Data Format
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| Each sample in the annotation file follows the format below:
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| ```json
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| {
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| "video_name": "6TiZ1coebWw_76s",
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| "category": "SFX",
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| "V2A_positive_prompt": "Realistic foley sound synchronized with the video.",
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| "negative_prompt": "music, background music, speech, singing",
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| "VT2A_positive_prompt": "Realistic foley sound of a fan rotating."
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| }
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| ```
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| ---
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| ## 4. Citation
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| If you use this dataset, please cite:
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| ```bibtex
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| @article{zhang2026vidaudio,
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| title={VidAudio-Bench: Benchmarking V2A and VT2A Generation across Five Audio Categories},
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| author={Zhang, Qian and Cao, Yuqin and Gao, Yixuan and Min, Xiongkuo},
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| journal={arXiv preprint arXiv:2604.10542},
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| year={2026}
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| }
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| ``` |
