Improved low bit-rate audio compression using reduced rank ICA instead of psychoacoustic modeling

Traditional audio coding is based on a perceptual compression paradigm that exploits psychoacoustic information to efficiently encode audio signals. Recently, extensive research has been conducted in order to understand how the brain encodes natural signals. These results suggest that the encoding process is very efficient in terms of redundancy reduction of the signal information. It could be that the psychoacoustic effects (such as the masking effect) are only a special case of a more general redundancy reduction mechanism that exists in the auditory pathway. Motivated by this work we propose a new audio coding scheme that is based on improved sound representation found by independent component analysis. Using a local linear, low rank, nonorthogonal transform, we remove additional redundancies in the signal. At low bitrates this coding scheme gives results superior to a legacy perceptual encoding scheme for different kinds of audio signals.