Speech Enhancement on Over-Complete Dictionary and Threshold Orthogonal Matching Pursuit

Abstract:

In order to suppress the noise, improve equipment's ability to further process information and improve the quality of voice, speech enhancement is often an important part of the speech signal preprocess. Contrastively analyze the characteristic that the clean speech signal coefficients in over-complete discrete cosine dictionary are much sparser than the traditional discrete cosine transform coefficients. Under noisy conditions, by setting the iterative threshold of orthogonal matching pursuit (OMP) algorithm, clean speech can be gotten, thus realize the speech enhancement. Simulation results of the signal waveform and spectrogram enhanced by the proposed algorithm are very similar to the original signal,comparative experiments also indicate that the signal to noise ratio (SNR) and the perceptual evaluation of speech quality (PESQ) score of the processed signal are superior to traditional discrete cosine transform (DCT).

• Periodical: Advanced Materials Research (Volumes 1044-1045)
• Pages: 1463-1468
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.1044-1045.1463
• Online since: October 2014
• Authors: Xiao Cui*, Wu Qing Zhang
• Keywords: Iterative Threshold, Orthogonal Matching Pursuit, Over-Complete Discrete Cosine Dictionary, Sparse Representation

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