Optimizing feature extraction for speech recognition

Chulhee Lee, Donghoon Hyun, Euisun Choi, Jinwook Go, Chungyong Lee

Research output: Contribution to journalArticlepeer-review

37 Citations (Scopus)


In this paper, we propose a method to minimize the loss of information during the feature extraction stage in speech recognition by optimizing the parameters of the mel-cepstrum transformation, a transform which is widely used in speech recognition. Typically, the mel-cepstrum is obtained by critical band filters whose characteristics play an important role in converting a speech signal into a sequence of vectors. First, we analyze the performance of the mel-cepstrum by changing the parameters of the filters such as shape, center frequency, and bandwidth. Then we propose an algorithm to optimize the parameters of the filters using the simplex method. Experiments with Korean digit words show that the recognition rate improved by about 4-7%.

Original languageEnglish
Pages (from-to)80-87
Number of pages8
JournalIEEE Transactions on Speech and Audio Processing
Issue number1
Publication statusPublished - 2003 Jan

Bibliographical note

Funding Information:
Manuscript received February 16, 2000; revised August 22, 2002. This work was supported in part by the Ministry of Information of Communication (MIC). The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Dirk van Compernolle. The authors are with the Department of Electrical and Electronic Engineering, Yonsei University, 120-749 Seoul, Korea (e-mail: chulhee@yonsei.ac.kr). Digital Object Identifier 10.1109/TSA.2002.805644

All Science Journal Classification (ASJC) codes

  • Software
  • Acoustics and Ultrasonics
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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