Speech Recognition Performance Improvement using Gamma-tone Feature Extraction Acoustic Model

감마톤 특징 추출 음향 모델을 이용한 음성 인식 성능 향상

  • Ahn, Chan-Shik (Dept. of Computer Engineering, The University of Kwangwoon) ;
  • Choi, Ki-Ho (Dept. of Computer Engineering, The University of Kwangwoon)
  • 안찬식 (광운대학교 컴퓨터공학과) ;
  • 최기호 (광운대학교 컴퓨터공학과)
  • Received : 2013.04.30
  • Accepted : 2013.07.20
  • Published : 2013.07.28


Improve the recognition performance of speech recognition systems as a method for recognizing human listening skills were incorporated into the system. In noisy environments by separating the speech signal and noise, select the desired speech signal. but In terms of practical performance of speech recognition systems are factors. According to recognized environmental changes due to noise speech detection is not accurate and learning model does not match. In this paper, to improve the speech recognition feature extraction using gamma tone and learning model using acoustic model was proposed. The proposed method the feature extraction using auditory scene analysis for human auditory perception was reflected In the process of learning models for recognition. For performance evaluation in noisy environments, -10dB, -5dB noise in the signal was performed to remove 3.12dB, 2.04dB SNR improvement in performance was confirmed.


Speech Recognition;Speech Signal Model;Feature Extraction;Acoustic Signal Model;Gamma-tone Energy


Supported by : 광운대학교