An Improved Single-Channel Speech Enhancement Algorithm with Maximum SNR Based on Modified Independent Component Analysis

Considering the shortcomings of unstable and low SNR of basic ICA (independent component analysis) in single-channel speech enhancement algorithm, a new ICA algorithm with maximum SNR for speech enhancement is presented in this article. By directly multiplying noisy speech with two-dimensional vectors and converting it into full column rank matrix, the two observed signals could be obtained. The obtained two observed signals have the properties of source signal without adding new noise so that it could ensure the system stability. ICA algorithm, which is modified by wavelet coefficients based on maximum SNR, is combined with the new two observed signals to realize the high efficiency and maximum SNR of the system. The experiments show that the presented algorithm is stable and it improves the SNR obviously.