Speech Signal Extraction Utilizing PCA-ICA Algorithm With a Non-Uniform Spacing Microphone Array
Sven Erik Nordholm, Siow Yong Low · 2006
Speech signal extraction is becoming more and more important as evidently displayed by its numerous applications such as mobile phones, conference equipments and surveillance. This paper presents a blind method to enhance a speech source of interest in noisy environments. The proposed technique consists of the principal component analysis (PCA) and the independent component analysis (ICA) to extract the speech signal. In an effort to overcome the small phase resolution due to the constraint on the inter-element distance, a non-uniform spacing PCA-ICA algorithm is suggested. By utilizing a different inter-element distance processing on each pair of microphones in a multistage fashion, a better separation is achieved. Results show better separation performance for the proposed method compared to the uniformly spaced microphone array.