Music Genre Classification of MPEG AAC Audio Data

In this paper, we propose a musical feature extracted from the bit stream of AAC (Advanced Audio Coding) compressed audio data without decoding to audio signals. We focus on the spectral data which are stored in the bit stream for representing the flatten MDCT (Modified Discrete Cosine Transform) of an audio signal. For computing the musical feature, we extract the spectral data and apply the Discrete Wavelet Transform (DWT) to the extracted spectral data. For musical genre classification, we use the discriminant analysis as a classifier. We experimented on 1,498 AAC compressed audio data collected from 10 musical genres and evaluated the performance of the musical feature. We got the maximum correct ratios 81.24%. The experiments showed that the musical feature based on the spectral data in the bit stream had good performance for genre classification in the MPEG-4 AAC compressed domain.