Feature extraction for robust speech recognition using a power-law nonlinearity and power-bias subtraction

@inproceedings{Kim2009FeatureEF,
  title={Feature extraction for robust speech recognition using a power-law nonlinearity and power-bias subtraction},
  author={Chanwoo Kim and Richard M. Stern},
  booktitle={INTERSPEECH},
  year={2009}
}
This paper presents a new feature extraction algorithm called PNCC that is based on auditory. Major new features of PNCC processing include the use of a power-law nonlinearity that replaces the traditional log nonlinearity used in MFCC coefficients, and a novel algorithm to suppress background excitation using medium-duration power estimation based on the ratio of the arithmetic mean to the geometric mean, and subtracting the medium-duration background power. Experimental results demonstrate… CONTINUE READING
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