---
language:
- en
license: cc-by-4.0
size_categories:
- 1K<n<10K
task_categories:
- audio-text-to-text
tags:
- audio-retrieval
- multimodal
- moment-retrieval
library_name: lighthouse
configs:
- config_name: default
  data_files:
  - split: train_en
    path: en/train.json
  - split: train_ja
    path: ja/train.json
  - split: valid_en
    path: en/val.json
  - split: valid_ja
    path: ja/val.json
  - split: test_en
    path: en/test.json
  - split: test_ja
    path: ja/test.json
---

# CASTELLA
This repository provides wav files used in [CASTELLA: Long Audio Dataset with Captions and Temporal Boundaries
](https://arxiv.org/abs/2511.15131). This dataset is originally provided in [GitHub](https://github.com/line/CASTELLA).

Each sample includes long audio containing some audio events with the temporal and textual annotation.

Project page: https://h-munakata.github.io/CASTELLA-demo/

Code: https://github.com/line/lighthouse

This repository only contains annotation data, not audio data.
Extracted features are available on [HF](https://huggingface.co/datasets/lighthouse-emnlp2024/CASTELLA_CLAP_features).

If you need raw audio files, use the download script in [GitHub](https://github.com/h-munakata/CASTELLA-audio)

# How to Use
```
from datasets import load_dataset

dataset = load_dataset("lighthouse-emnlp2024/CASTELLA")

for d in dataset["train_en"]:
    print(d)
    break
>>> {'yid': '-0awng26xQ8', 'global_caption': 'A man is talking while driving, stops somewhere, then drives again', ...}
```

## 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},
}
```