Create README.md

README.md

@@ -1,3 +1,81 @@
----
-license: mit
----
+---
+license: cc-by-nc-4.0
+language:
+- en
+- ko
+tags:
+- music
+- music-information-retrieval
+- plagiarism-detection
+- music-similarity
+task_categories:
+- audio-classification
+size_categories:
+- n<1K
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: smp_dataset.csv
+arxiv: 2601.21260
+---
+
+# Similar Music Pair (SMP) Dataset
+
+The SMP (Segment-based Music Plagiarism) dataset contains music plagiarism 
+detection pairs with temporal segment annotations. Each row represents a pair 
+of songs with identified similar segments.
+
+This dataset accompanies the paper 
+[Music Plagiarism Detection: Problem Formulation and a Segment-based Solution](https://arxiv.org/abs/2601.21260).
+
+- Code: https://github.com/Mippia/Music-Plagiarism-Detection
+- Demo: https://huggingface.co/spaces/mippia/MPD-demo
+- Project page: https://mippia.github.io/icassp-mpd/
+
+## Dataset Structure
+
+| Column | Description |
+| --- | --- |
+| `ori_title` | Title of the original song |
+| `comp_title` | Title of the comparison song |
+| `ori_link` | YouTube link to the original song |
+| `comp_link` | YouTube link to the comparison song |
+| `relation` | Relationship type (e.g., `plag` for plagiarism) |
+| `ori_times` | List of start times (seconds) of similar segments in the original song |
+| `comp_times` | List of start times (seconds) of similar segments in the comparison song |
+| `pair_number` | Unique identifier for song pairs |
+| `acoustic_idx` | Unique identifier for segment pairs |
+
+Time annotations are JSON-formatted lists; `ori_times[i]` and `comp_times[i]` 
+correspond to the same matching segment between the two songs.
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("mippia/SMP-dataset")
+print(dataset["train"][0])
+```
+
+## Notes
+
+- **Audio is not included.** Only YouTube links and temporal annotations are 
+  provided. Users must retrieve audio from YouTube themselves.
+- The dataset includes both English and Korean songs across multiple genres.
+
+## Citation
+
+```bibtex
+@inproceedings{go2026mpd,
+  title={Music Plagiarism Detection: Problem Formulation and a Segment-based Solution},
+  author={Go, Seonghyeon and Kim, Yumin},
+  booktitle={ICASSP},
+  year={2026}
+}
+```
+
+## License
+
+Released under CC BY-NC 4.0 for non-commercial research use.