ICA-based Noise Reduction for Mobile Phone Speech Communication
Zhipeng Zhang, Minoru Etoh · 2007
We propose a frequency-domain independent component analysis (ICA) with robust and computationally-light post processing method for background noise reduction in mobile phone speech communication. In our scenario, multi-source signal separation is not the target, but noise reduction is the primal one. This primal target characterizes our approach that promotes a new physical constraint, in other words, we place a restriction on the amplitude range of the transfer functions rather than assuming that the amplitudes are constant. When there are diffraction, obstacles and reflections in the real-world environment, it is better to assume that transfer function amplitude (derived from the distance to the mouth) varies within a certain range. Our two-microphone experiment shows that the ICA-based noise reduction significantly improves speech recognition performance especially in severe noise conditions.