dim-sim

<p>The&nbsp;<strong>dim-sim</strong>&nbsp;dataset is a collection of user-annotated music similarity triplet ratings used to evaluate music similarity search and related algorithms. Our similarity ratings are linked to the&nbsp;<a href="http://millionsongdataset.com/">Million Song Dataset (MSD)</a>&nbsp;and were collected for the following paper:</p> <p>&nbsp;</p> <p><a href="https://ieeexplore.ieee.org/document/9053442/">Disentangled Multidimensional Metric Learning for Music Similarity</a><br> Jongpil Lee, Nicholas J. Bryan, Justin Salamon, Zeyu Jin, and Juhan Nam.<br> Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP). IEEE, 2020.</p> <pre><code>@inproceedings{Lee2019MusicSimilarity, title={Disentangled Multidimensional Metric Learning For Music Similarity}, author={Lee, Jongpil and Bryan, Nicholas J. and Salamon, Justin and Jin, Zeyu, and Nam, Juhan}, booktitle={Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, year={2020}, organization={IEEE} }</code></pre> <p>We kindly request that articles and other works in which this dataset is used cite the paper as listed above.</p> <p>Please see our paper or visit&nbsp;<a href="https://jongpillee.github.io/multi-dim-music-sim">https://jongpillee.github.io/multi-dim-music-sim</a>&nbsp;for more information.&nbsp;</p>