A new group delay-based feature for robust speech recognition

E. Loweimi, Seyed Mohammad Ahadi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

In this paper we present a novel feature extraction algorithm based on group delay function for robust speech recognition. The modified group delay function (MODGDF) is the main feature extraction method based on group delay function, generally used for robust speech recognition. The recognition tests indicate this feature does not provide notably better results in the presence of additive noise in comparison with MFCC. In the presence of convolutional noise, the performance of MODGDF is considerably lower than MFCC. The method proposed in this paper is simple and makes more efficient utilization of the high resolution property of GDF. It is formed from three main parts which are signal modeling, GDF computation based on extracted model, and compression. The recognition results obtained over AURORA 2.0 task indicate its superior performance in comparison with MODGDF and MFCC.
Original languageEnglish
Title of host publication2011 IEEE International Conference on Multimedia and Expo
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-5
Number of pages5
ISBN (Electronic)978-1-61284-349-0
ISBN (Print)978-1-61284-348-3
DOIs
Publication statusPublished - 1 Jul 2011
Event2011 IEEE International Conference on Multimedia and Expo - Barcelona, Spain
Duration: 11 Jul 201115 Jul 2011
http://www.ieee-icme.org/icme2011/

Conference

Conference2011 IEEE International Conference on Multimedia and Expo
Abbreviated titleICME 2011
Country/TerritorySpain
CityBarcelona
Period11/07/1115/07/11
Internet address

Keywords / Materials (for Non-textual outputs)

  • Delay
  • Speech
  • Mel frequency cepstral coefficient
  • Speech recognition
  • Feature extraction
  • Computational modeling
  • Discrete cosine transforms
  • Robust speech recognition
  • group delay function
  • signal modeling
  • compression

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