Data reduction of audio by exploiting musical repetition

Abstract

This paper presents and evaluates a method of audio compression specifically designed to exploit the natural repetition that occurs within musical audio. Our system is entitled Audio Compression Exploiting Repetition (ACER). ACER is a perceptual technique, but one that does not consider exploiting masking, but rather attempts to apply the principles of Lempel-Ziv and run-length encoding, by substituting audio sequences for numeric or character strings. The ACER procedure applies a pseudo exhaustive search process and spectral difference grading. Since ACER exploits musical structure, the amount of data reduction achieved varies from piece-to-piece. The system is described before results on a corpus of material are presented. The analysis shows moderate amounts of data reduction take place whilst the system is operating within parameters designed to maintain high-levels of perceptual audio quality, whilst lower rates of perceptual quality yield greater data reduction. Objective quality evaluations are conducted that reveal degradation in fidelity that is relative to the compression parameters.