A perception-and PDE-based nonlinear transformation for processing spoken words

Yingyong Qi Jack Xin

Geometric Modeling and Processing mathscidoc:1912.43897

Physica D: Nonlinear Phenomena, 149, (3), 143-160, 2001.2
Speech signals are often produced or received in the presence of noise, which is known to degrade the performance of a speech recognition system. In this paper, a perception-and PDE-based nonlinear transformation was developed to process spoken words in noisy environment. Our goal is to distinguish essential speech features and suppress noise so that the processed words are better recognized by a computer software. The nonlinear transformation was made on the spectrogram (short-term Fourier spectra) of speech signals, which reveals the signal energy distribution in time and frequency. The transformation reduces noise through time adaptation (reducing temporally slowly varying portions of spectra) and enhances spectral peaks (formants) by evolving a focusing quadratic fourth-order PDE. Short-term spectra of speech signals were initially divided into three (low, mid and high) frequency bands based
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  title={A perception-and PDE-based nonlinear transformation for processing spoken words},
  author={Yingyong Qi, and Jack Xin},
  booktitle={Physica D: Nonlinear Phenomena},
Yingyong Qi, and Jack Xin. A perception-and PDE-based nonlinear transformation for processing spoken words. 2001. Vol. 149. In Physica D: Nonlinear Phenomena. pp.143-160. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191224210518801819461.
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