Scalability issues in HMM-based Audio Fingerprinting

TitleScalability issues in HMM-based Audio Fingerprinting
Publication TypeConference Paper
Year of Publication2004
Conference Name International Conference on Multimedia and Expo
AuthorsBatlle, E., Masip J., Guaus E., & Cano P.
Pagination735-738
Conference Start Date27/06/2004
Conference LocationTaipei, 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.

intranet