We present a framework for audio fingerprint- ing, rather general in its essence, but especially tuned for being used in the context of broadcast monitoring. We efficiently implemented a robust fingerprinting algorithm and a suitable retrieval method. Ample sections are devoted to strategies for improving both the reliability and the speed of the overall system. The outcomes of plentiful experiments on a database of 100 000 songs are analyzed, and two common kinds of distortion (pitching and thermal noise) are investigated. To better drive design decisions, we also provide in-depth discussion on the scalability of the indexing algorithm.
A Framework for Robust Audio Fingerprinting
BELLETTINI, Carlo;MAZZINI, Gianluca
2010
Abstract
We present a framework for audio fingerprint- ing, rather general in its essence, but especially tuned for being used in the context of broadcast monitoring. We efficiently implemented a robust fingerprinting algorithm and a suitable retrieval method. Ample sections are devoted to strategies for improving both the reliability and the speed of the overall system. The outcomes of plentiful experiments on a database of 100 000 songs are analyzed, and two common kinds of distortion (pitching and thermal noise) are investigated. To better drive design decisions, we also provide in-depth discussion on the scalability of the indexing algorithm.I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
