We propose a novel principle based on Complex Spectrum Circle Centroid
(CSCC) for restoring complex spectrum of the target signal from multiple
microphone input signals in a noisy environment. If noise arrives at
multiple microphones with different time delays relative to the target
signal, the observed noisy signals lie on a circle in the complex
spectrum plane from which the target signal is restored by finding the
centroid of the circle. Unlike most of existing methods for noise
reduction such as ICA, AMNOR and beamforming, this non-linear operation
is applicable to any type of noise including non-stationary, moving,
signal-correlated, non-planar, and interfering speakers, without
identifying the noise direction and training parameters.
The proposed method was evaluated with speech recognition experiments in
simulated noisy environments and was shown to improve the word accuracy
close to the clean speech recognition rate of 89.4% in the case of a
single spoken noise, and from 0% with one microphone to 60.6% with 8
microphones in the case of 3 interfering speakers. The properties of
this new method is further discussed theoretically and experimentally.