Facebook pixel tracking

The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

Contact Info
Email info@thesai.org
Website thesai.org
Follow Us
Contact Info
Email info@thesai.org
Follow Us
Research Article | Open Access |

Physiologically Motivated Feature Extraction for Robust Automatic Speech Recognition

Author 1: Ibrahim Missaoui Author 2: Zied Lachiri
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 4 · Published 2016

DOI: https://doi.org/10.14569/IJACSA.2016.070438

Download PDF Cite Call for Papers

Abstract

In this paper, a new method is presented to extract robust speech features in the presence of the external noise. The proposed method based on two-dimensional Gabor filters takes in account the spectro-temporal modulation frequencies and also limits the redundancy on the feature level. The performance of the proposed feature extraction method was evaluated on isolated speech words which are extracted from TIMIT corpus and corrupted by background noise. The evaluation results demonstrate that the proposed feature extraction method outperforms the classic methods such as Perceptual Linear Prediction, Linear Predictive Coding, Linear Prediction Cepstral coefficients and Mel Frequency Cepstral Coefficients.

Keywords

Feature extraction Two-dimensional Gabor filters Noisy speech recognition

How to Cite this Article

Missaoui, I., & Lachiri, Z. (2016). Physiologically Motivated Feature Extraction for Robust Automatic Speech Recognition. International Journal of Advanced Computer Science and Applications, 7(4). https://doi.org/10.14569/IJACSA.2016.070438

Missaoui, Ibrahim, and Zied Lachiri. "Physiologically Motivated Feature Extraction for Robust Automatic Speech Recognition." International Journal of Advanced Computer Science and Applications, vol. 7, no. 4, 2016, https://doi.org/10.14569/IJACSA.2016.070438.

@article{Missaoui2016,
  title     = {Physiologically Motivated Feature Extraction for Robust Automatic Speech Recognition},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {4},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Ibrahim Missaoui and Zied Lachiri},
  doi       = {10.14569/IJACSA.2016.070438},
  url       = {https://doi.org/10.14569/IJACSA.2016.070438}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

Back to Issue
IJACSA Journal Cover

IJACSA