Compressive Coding of Stereo Audio Signals Extracting Sparseness among Sound Sources with Independent Component Analysis

In this paper we propose a new compressive coding method of stereo audio signals extracting sparseness among sound sources by using independent component analysis. Some researchers have proposed a compressive coding method of multi-channel audio called binaural cue coding (BCC), and the ISO/MPEG standardization group discusses standard of next generation audio based on BCC. BCC has an underlying model assuming existence of only a single sound source in each subband of the multi-channel audio signal. Mismatch of this model often occurs and as a result quality of reconstructed multi-channel signal degrades. To extract the time-frequency grids where only a single source exists, we apply independent component analysis (ICA) to stereo signals. Using this analysis, a single dominant source can be chosen efficiently in each of frequency bins. In addition, transfer functions to reconstruct stereo signal from the dominant source is also extracted by ICA. Experiments based on both objective and subjective evaluations ascertains efficiency of the proposed method.