Enhanced LBP texture features from time frequency representations for acoustic scene classification

This paper introduces the use of local binary patterns (LBP) extracted from a time-frequency representation (TFR) for acoustic scene classification. As LBP provides a description of the global TFR texture we propose a novel zoning mechanism that provides a simple solution to extract spectrally relevant local features which better characterize the audio TFRs. To further improve the classification performance, we perform feature and score level fusion of the proposed LBP (with zoning) with histogram of gradients (HOG) of the TFR images. Our technique demonstrates an improved performance by achieving a classification accuracy of 95.2% using a fusion of time-frequency derived features.