A Novel Magnitude-Squared Spectrum Cost Function for Speech Enhancement

Authors

  • Huan Zhao Hunan University
  • Zhiqiang Lu Hunan University
  • Fei Yu Nanjing University of Posts and Telecommunicationsy
  • Cheng Xu Nanjing University of Posts and Telecommunicationsy

DOI:

https://doi.org/10.5755/j01.eee.122.6.1812

Abstract

In Bayesian approaches for speech enhancement, the enhanced speech is estimated by minimizing the Bayes risk. In detail, an estimate of the clean speech is derived by minimizing the expectation of a cost function. Various estimators have been derived by the classic cost function, squared-error cost function, and “hit-or-miss” function. However, absolute error function was paid less attention. In this paper, we consider a magnitude-squared spectrum (MSS) motivated estimator for speech enhancement based on statistics and Bayesian cost function in the frequency domain. Specifically, we derive a novel estimator of which the cost function is the absolute error distortion measure of the MSS. By studying experimental results with NOIZEUS database, we find that the performance of the proposed scheme can achieve a significant noise reduction and a better speech quality as compared to minimum mean-squared error (MMSE) estimator of the MSS. Ill. 1, bibl. 14, tabl. 2 (in English; abstracts in English and Lithuanian)

DOI: http://dx.doi.org/10.5755/j01.eee.122.6.1812

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Published

2012-06-07

How to Cite

Zhao, H., Lu, Z., Yu, F., & Xu, C. (2012). A Novel Magnitude-Squared Spectrum Cost Function for Speech Enhancement. Elektronika Ir Elektrotechnika, 122(6), 11-14. https://doi.org/10.5755/j01.eee.122.6.1812

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Section

SYSTEM ENGINEERING, COMPUTER TECHNOLOGY