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Scalability issues in HMM-based Audio Fingerprinting

Title Scalability issues in HMM-based Audio Fingerprinting
Publication Type Conference Paper
Year of Publication 2004
Conference Name International Conference on Multimedia and Expo
Authors Batlle, E. , Masip J. , Guaus E. , & Cano P.
Pagination 735-738
Conference Start Date 27/06/2004
Conference Location Taipei, Taiwan
Abstract

Audio fingerprinting technologies allow the identification of audio content without the need of an external metadata or watermark embedding. These audio fingerprint technologies work by extracting a content-based compact digest that summarizes a recording and comparing them with a previously extracted fingerprint database. In this paper we present a fingerprint scheme that is based on Hidden Markov Models. This approach achieves a high compaction of the audio signal by exploiting structural redundancies on music and robustness to distortions thanks to the stochastic modeling. In this paper, we present the basic functionality of the system as well as some results.