Machine learningDistance metrics and similarity
Music Similarity Measure
Music similarity measures are computational methods for assessing how musically related two audio recordings are. Introduced by Logan (2001), similarity measures enable content-based music recommendation, playlist generation, and music discovery. Unlike fingerprinting, which identifies the same song, similarity measures gauge stylistic, timbral, and structural resemblance between different songs. Measures can be acoustic (comparing spectral features), high-level (genre, mood), or hybrid.
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Sources
- Logan, B., & Salomon, A. (2001). A music similarity function based on song structure. In Proceedings of the International Conference on Music Information Retrieval. link ↗
- Mandel, M. I., & Ellis, D. P. (2005). Song-level features and support vector machines for music classification. In Proceedings of the International Society for Music Information Retrieval Conference. link ↗
- Serra, X., Gómez, E., Herrera, P., & Gómez, P. (2008). Chroma binary similarity and local alignment for cover song identification. IEEE Transactions on Audio, Speech, and Language Processing, 16(5), 1029-1037. DOI: 10.1109/TASL.2008.924519 ↗