A Highly Robust Audio Fingerprinting System

By Jaap Haitsma, Ton Kalker. International Society for Music Information Retrieval Conference, 2002

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An Industrial Strength Audio Search Algorithm (2003, background): “Furthermore, for applications such as radio monitoring, search times on the order of a few milliseconds per query are attained, even on a massive music database.”
Embedding Watermarks into Deep Neural Networks (2017, unknown): “Digital fingerprinting is an alternative to the watermarking approach for persistent identification of images [2], video [20, 31], and audio clips [1, 11].”
A Review of Audio Fingerprinting (2005, methodology): “deal with false positives have been explicitly treated for instance in [4, 18, 34].”
Earthquake detection through computationally efficient similarity search (2015, background): “…in massive data sets ( 23 ); applications include identifying similar files in a large file system ( 24 ), finding near-duplicate Web pages ( 25 ), detecting plagiarism in documents ( 26 ), and recognizing similar audio clips for music identification ( 27 ), such as in the Shazam mobile app ( 28 ).”
Factors in automatic musical genre classification of audio signals (2003, methodology): “Once copyright protection can be enforced using techniques such as audio fingerprinting [I] it is very likely that all of recorded music will he available digitally.”
Implementation and Benchmarking of Perceptual Image Hash Functions (2010, background): “Haitsma and Kalker (2002b) [17] suggest audio Fingerprinting to enhance the security of watermarks in the context of copy attacks.”