Frequency-temporal filtering for a robust audio fingerprinting scheme in real-noise environments

Abstract

In a real environment, sound recordings are commonly distorted by channel and background noise, and the performance of audio identification is mainly degraded by them. Recently, Philips introduced a robust and efficient audio fingerprinting scheme applying a differential (high-passfiltering) to the frequency-time sequence of the perceptual filter-bank energies. In practice, however the robustness of the audio fingerprinting scheme is still important in a real environment. In this letter we introduce alternatives to the frequency-temporal filtering combination for an extension method of Philips' audio fingerprinting scheme to achieve robustness to channel and background noise under the conditions of a real situation. Our experimental results show that the proposed filtering combination improves noise robustness in audio identification.