mippia/SMP_dataset

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.

• 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

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

@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 MIT License.