Datasets:
Tasks:
Audio-Text-to-Text
Modalities:
Text
Formats:
webdataset
Languages:
English
Size:
1K - 10K
ArXiv:
License:
| license: cc-by-4.0 | |
| language: | |
| - en | |
| tags: | |
| - multimodal | |
| - audio-retrieval | |
| - moment-retrieval | |
| size_categories: | |
| - 1K<n<10K | |
| task_categories: | |
| - audio-text-to-text | |
| # CASTELLA CLAP features | |
| This repository contains audio and text features of [CASTELLA dataset](https://arxiv.org/abs/2511.15131) extracted by CLAP. | |
| - Using these features, we can reproduce the audio moments retrieval using CASTELLA, which is used in [lighthouse](https://github.com/line/lighthouse). | |
| - Please also check [demo page](https://h-munakata.github.io/CASTELLA-demo/). | |
| ## How to Download? | |
| Run the following script: | |
| ```python | |
| from huggingface_hub import snapshot_download | |
| repo_id = "lighthouse-emnlp2024/CASTELLA_CLAP_features" | |
| local_dir = "./" | |
| downloaded_path = snapshot_download( | |
| repo_id=repo_id, | |
| repo_type="dataset", | |
| local_dir=local_dir, | |
| allow_patterns="*.tar.gz", | |
| ) | |
| ``` | |
| ## How to Use on Lighthouse | |
| The `.tar.gz` files should be decompressed by following shell commands: | |
| ```bash | |
| mkdir -p {LIGHTHOUSE_PATH}/features/castella/clap | |
| mkdir -p {LIGHTHOUSE_PATH}/features/castella/clap_text | |
| tar -zxvf clap.tar.gz -C {LIGHTHOUSE_PATH}/features/castella/clap | |
| tar -zxvf clap_text.tar.gz -C {LIGHTHOUSE_PATH}/features/castella/clap_text | |
| ``` | |
| ## Citation | |
| ```bibtex | |
| @article{munakata2025castella, | |
| title={CASTELLA: Long Audio Dataset with Captions and Temporal Boundaries}, | |
| author={Munakata, Hokuto and Takehiro, Imamura and Nishimura, Taichi and Komatsu, Tatsuya}, | |
| journal={arXiv preprint arXiv:2511.15131}, | |
| year={2025}, | |
| } | |
| ``` |