Music Genre Classification of MPEG AAC Audio Data

Abstract

In this paper, we propose a musical feature extracted from the bitstream of AAC (Advanced Audio Coding) compressed audio data without decoding to audio signals. We focus on the spectral data which are stored in the bitstream 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 bitstream had good performance for genre classification in the MPEG-4 AAC compressed domain.

A New Genre Classification with the Colors of Music

“…Automatic classification of files requires intelligent systems, which understand the content of the files. Genre classification of audio data [1], paintings [2], web pages [3] and music [4] are some of the studies. Music genre is a label defined by human categorizing the music.…”