Modulation frequency features for audio fingerprinting

Abstract

This paper explores modulation frequency features with subband normalization for audio identification. Our main goal is to find features for audio fingerprinting that are invariant to time and frequency distortions, both unintentional and intentional. Two-dimensional features, called “joint acoustic and modulation frequency,” are proposed. The paper describes these features and corresponding cross entropy classification. Experimental results show that standard spectral features are inadequate when frequency distortion occurs, as in low bit rate coding or equalization. In contrast, our proposed normalized modulation frequency features can provide accurate fingerprints, even when time and frequency distortions are imposed on music passages.