| # Auto-ACD | |
| Auto-ACD is a large-scale, high-quality, audio-language dataset, building on the prior of robust audio-visual correspondence in existing video datasets, VGGSound and AudioSet. | |
| - **Homepage:** https://auto-acd.github.io/ | |
| - **Paper:** https://huggingface.co/papers/2309.11500 | |
| - **Github:** https://github.com/LoieSun/Auto-ACD | |
| ## Analysis | |
|  | |
| Auto-ACD</strong>, comprising over <strong>1.9M </strong> audio-text pairs. | |
| As shown in figure, The text descriptions in Auto-ACD contain <strong>long texts (18 words)</strong> and <strong>diverse vocabularies (23K)</strong>, and provide information about the <strong>surrounding auditory environment</strong>(data point with <strong>shadow</strong>) in which sounds take place. | |
| ## Download | |
| We provide a csv file. For each data pairs, we provide YouTube URLs and generated caption. Each line in the csv file has columns defined by here. | |
| ``` | |
| # YouTube ID, caption | |
| ``` | |
| ## Dataset Preview | |
|  | |