Subband conversion for feature extraction from compressed audio

We describe an efficient conversion method, which directly converts a desired spectral representation from compressed audio material. The conversion method provides a feature extraction algorithm with a suitable complex frequency representation of an audio signal. The presented conversion allows us to trade off computational complexity with accuracy. We then test several operating points with an MPEG audio feature extraction system. That leads, in general, to a reduction of the computational complexity from O (N log N) to O(N), compared to the conventional method of first decoding and then applying the DFT to the resulting time domain audio signal.