• DOI:10.3844/jcssp.2016.56.61
Corpus ID: 28844088

Feature Extraction Method for Improving Speech Recognition in Noisy Environments

@article{Zouhir2016FeatureEM,
  title={Feature Extraction Method for Improving Speech Recognition in Noisy Environments},
  author={Youssef Zouhir and Ka{\"i}s Ouni},
  journal={J. Comput. Sci.},
  year={2016},
  volume={12},
  pages={56-61}
}

Youssef Zouhir, Kaïs Ouni

Published 2016

Computer Science

J. Comput. Sci.

The paper presents a feature extraction method, named as Normalized Gammachirp Cepstral Coefficients (NGCC) that incorporates the properties of the peripheral auditory system to improve robustness in noisy speech recognition. The proposed method is based on a second order low-pass filter and normalized gammachirp filterbank to emulate the mechanisms performed in the outer/middle ear and cochlea. The speech recognition performance of this method is conducted on the speech signals in real-world… CONTINUE READING

View via Publisher

thescipub.com

Save to Library

Create Alert

Cite

Launch Research Feed