A New Biologically Inspired Fuzzy Expert System-Based Voiced/Unvoiced Decision Algorithm for Speech Enhancement

In this paper, we propose a speech enhancement approach for a single-microphone system. The main idea is to apply a specific transformation on the speech signal depending on the voicing state of the signal. We apply a voiced/unvoiced algorithm based on the multi-scale product analysis with the use of fuzzy logic to make more cognitively inspired use of speech information. A comb filtering is applied on the voiced frames of the noisy speech signal, and a spectral subtraction is operated on the unvoiced frames of the same signal. Further, the harmonics are enhanced by performing a designed comb filtering using an adjustable bandwidth. The comb filter is tuned by an accurate fundamental frequency estimation method. The fundamental frequency estimation method is based on computing the multi-scale product analysis of the noisy speech. Experimental results show that the proposed approach is capable of reducing noise in adverse noise environments with little speech degradation and outperforms several competitive methods.