Blind source separation of acoustic mixtures using time-frequency domain independent component analysis

Authors:
D. S. Jayarman;G. Sitaraman;R. Seshadri
Affiliations:
PSG Coll. of Technol., Coimbatore, India;Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, Que., Canada;VLSI Circuit Design & Test Dept., Singapore, Singapore
Venue:
ICCS '02 Proceedings of the The 8th International Conference on Communication Systems - Volume 02
Year:
2002

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Abstract

Blind source separation of acoustic mixtures aims at providing a solution to the classical cocktail-party problem. The inherent delays and convolutions in microphone recordings, entails a modification in the independent component analysis (ICA), which achieves separation by making the assumption of statistical independence of source signals that are linearly combined. The proposed algorithm provides a solution for the blind source separation problem by shifting the domain of the problem to the time-frequency domain and applying ICA to each of the frequency components individually. Satisfactory results were achieved for speech-music as well as speech-speech separation by adopting the time-frequency domain ICA.