Speech enhancement based on a few shapes of speech spectrum

In this paper, we propose a speech enhancement method based on a few shapes of speech spectrum. First, we utilizes Minima Controlled Recursive Averaging (MCRA) algorithm to estimate the noise instead of training the noise codebooks used in conventional method. Then, the spectral shapes and the spectral gains of speech and noise are optimized by minimizing the spectral distortion between the noisy speech and the combination of noise and speech. Next, the normalized cross-correlation coefficients between the spectra of noisy speech and noise are used to modify the spectral gains of speech and noise. Finally, the noisy speech is passed through the reconstructed Wiener filter to obtain the enhanced speech. The objective and subjective tests show that the performance of removing annoying background noise occurred in the unvoiced segments or silence segments is much better than the conventional codebook-based method.