Robust matching of audio signals using spectral flatness features

Stimulated by the ever-increasing amount of available multimedia data, content-related techniques for the management of audio material have received much interest recently. This paper discusses the problem of robust identification of audio signals by matching them to a known reference. In order to perform well under realworld conditions, the matching process needs to rely on features which are robust with respect to common signal distortions. A family of suitable features with favorable properties is proposed and evaluated for their recognition performance. Applications of signal matching, including fingerprinting, are discussed.