Create README.md

README.md

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+---
+language:
+  - en
+license: other
+task_categories:
+  - audio-classification
+  - text-to-audio
+tags:
+  - audio-retrieval
+  - audio-captioning
+  - DCASE
+  - CLAP
+  - contrastive-learning
+pretty_name: Clotho Development Subset
+size_categories:
+  - 1K<n<10K
+---
+
+# Clotho Development Subset
+
+A sampled subset (~3GB) of the [Clotho v2.1](https://zenodo.org/record/3490684) development split, packaged for quick experimentation with audio-text retrieval pipelines.
+
+## 📋 Dataset Description
+
+This dataset is a convenience subset of the **Clotho** audio captioning dataset, created for rapid prototyping and testing of audio-text retrieval models (e.g., CLAP fine-tuning) on limited compute.
+
+- **Source**: Clotho v2.1 (development split)
+- **Original Authors**: K. Drossos, S. Lipping, T. Virtanen
+- **Original Paper**: [Clotho: An Audio Captioning Dataset](https://arxiv.org/abs/1910.09387)
+
+## 📊 Dataset Structure
+
+### Splits
+
+| Split | Samples | Description |
+|-------|---------|-------------|
+| train | ~1,300  | Training set (80%) |
+| test  | ~330    | Test set (20%) |
+
+### Features
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `file_name` | `string` | Original filename from Clotho |
+| `audio` | `Audio` | Audio waveform, 44.1kHz |
+| `caption_1` | `string` | Human-written caption #1 |
+| `caption_2` | `string` | Human-written caption #2 |
+| `caption_3` | `string` | Human-written caption #3 |
+| `caption_4` | `string` | Human-written caption #4 |
+| `caption_5` | `string` | Human-written caption #5 |
+
+### Audio Details
+
+- **Duration**: 15–30 seconds per clip
+- **Sample Rate**: 44,100 Hz
+- **Channels**: Mono
+- **Format**: WAV (stored as Parquet/Arrow on Hub)
+
+## 🚀 Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("your-username/clotho-dev-sample")
+
+# Access a sample
+sample = ds["train"][0]
+print(sample["caption_1"])   # "A dog barks in the distance"
+print(sample["audio"])       # {'array': array([...]), 'sampling_rate': 44100}
+```
+
+### With CLAP
+
+```python
+from transformers import ClapProcessor, ClapModel
+
+processor = ClapProcessor.from_pretrained("laion/clap-htsat-unfused")
+model = ClapModel.from_pretrained("laion/clap-htsat-unfused")
+
+sample = ds["train"][0]
+inputs = processor(
+    audios=sample["audio"]["array"],
+    sampling_rate=sample["audio"]["sampling_rate"],
+    text=sample["caption_1"],
+    return_tensors="pt",
+    padding=True,
+)
+outputs = model(**inputs)
+```
+
+## ⚠️ Important Notes
+
+- This is a **subset** (~43%) of the full Clotho development split, sampled randomly with `seed=42`
+- For official benchmarking, use the full Clotho dataset from [Zenodo](https://zenodo.org/record/3490684)
+- This subset is intended for **pipeline testing and prototyping only**
+
+## 📄 Citation
+
+If you use this dataset, please cite the original Clotho paper:
+
+```bibtex
+@inproceedings{drossos2020clotho,
+  title={Clotho: An Audio Captioning Dataset},
+  author={Drossos, Konstantinos and Lipping, Samuel and Virtanen, Tuomas},
+  booktitle={ICASSP 2020 - IEEE International Conference on Acoustics, Speech and Signal Processing},
+  pages={736--740},
+  year={2020},
+  organization={IEEE}
+}
+```
+
+## 🏷️ License
+
+This dataset follows the original Clotho license. Audio clips are sourced from [Freesound](https://freesound.org/) under Creative Commons licenses. Please refer to the [original dataset](https://zenodo.org/record/3490684) for full license details.