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CHMM Modeling using LMS Algorithm for Continuous Speech Recognition Improvement

연속 음성 인식 향상을 위해 LMS 알고리즘을 이용한 CHMM 모델링

  • 안찬식 (광운대학교 컴퓨터공학과) ;
  • 오상엽 (가천대학교 IT대학 인터랙티브미디어학과)
  • Received : 2012.10.28
  • Accepted : 2012.11.20
  • Published : 2012.12.31

Abstract

In this paper, the echo noise robust CHMM learning model using echo cancellation average estimator LMS algorithm is proposed. To be able to adapt to the changing echo noise. For improving the performance of a continuous speech recognition, CHMM models were constructed using echo noise cancellation average estimator LMS algorithm. As a results, SNR of speech obtained by removing Changing environment noise is improved as average 1.93dB, recognition rate improved as 2.1%.

Keywords

Echo Noise Cancellation;Average Estimator;LMS(Least Mean Square) filter;adaptive filter;CHMM(Continuous Hidden Markov Model) Model

Acknowledgement

Supported by : 가천대학교