A Framework for Robust Audio Fingerprinting

We present a framework for audio fingerprinting,
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.