Machine learningHashing and identification
Audio Fingerprinting
Audio fingerprinting is a technique for creating a compact, robust identifier (fingerprint) for audio recordings that uniquely represents the content while being tolerant to modifications such as compression, noise, or time-shifting. Introduced by Haitsma and Kalker (2002), it underlies music identification services like Shazam and is critical for copyright enforcement, music matching, and library deduplication. A fingerprint is not a waveform hash; it captures perceptual content and remains stable across reasonable audio alterations.
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Sources
- Haitsma, J., & Kalker, T. (2002). A highly robust audio fingerprinting system. In Proceedings of the International Symposium on Music Information Retrieval. link ↗
- Wang, A. L. (2003). An industrial-strength audio search algorithm. In Proceedings of the International Symposium on Music Information Retrieval. link ↗
- Cano, P., Batlle, E., Kalker, T., & Haitsma, J. (2005). A review of audio fingerprinting. Journal of the Audio Engineering Society, 53(9), 804-825. link ↗