서지주요정보
잡음하 음성 인식에서 선택적 주의 집중을 이용한 독립 요소 해석 기법의 성능 향상 = Improved independent component analysis using selective attention for noisy speech recognition
서명 / 저자 잡음하 음성 인식에서 선택적 주의 집중을 이용한 독립 요소 해석 기법의 성능 향상 = Improved independent component analysis using selective attention for noisy speech recognition / 배언민.
발행사항 [대전 : 한국과학기술원, 2000].
Online Access 원문보기 원문인쇄

소장정보

등록번호

8010470

소장위치/청구기호

학술문화관(문화관) 보존서고

MEE 00041

휴대폰 전송

도서상태

이용가능

대출가능

반납예정일

리뷰정보

초록정보

Recently, blind signal separation by Independent Component Analysis(ICA) has been received attention because of its potential applications in various fields of signal processing. ICA finds a linear coordinate system(the unmixing system) so that the resulting signals are statistically independent from each other as possible. ICA depends on several assumptions such that sources are mutually independent and linearly mixed. These assumptions restrict the performance of ICA within few applications of real environments where all of the assumptions are satisfied. For most applications of ICA in real environments, it is necessary to release of all assumptions or compensate for these restrictions. In this work, an algorithm to improve the performance of ICA was proposed. It can compensate for the restrictions of ICA by feedback operations from a classifier to the ICA network. Under the assumption of the stationary environment, providing additional information of the mixing environment for the ICA network can improve the recognition performance. The proposed algorithm performs iterative feedback operations to provide the additional information of the classifier for the ICA network. The algorithm was applied to isolated-word speech recognition in noisy environments. Mel-Frequency Cepstral Coefficient(MFCC) was used for feature extraction and Multi-Layer Perceptron(MLP) was the classifier. For the convolved mixture of speech and noise recorded in real environment, the algorithm improved the recognition performance and showed robustness against parametric changes.

서지기타정보

서지기타정보
청구기호 {MEE 00041
형태사항 vii, 49 p. : 삽도 ; 26 cm
언어 한국어
일반주기 저자명의 영문표기 : Un-Min Bae
지도교수의 한글표기 : 이수영
지도교수의 영문표기 : Soo-Young Lee
학위논문 학위논문(석사) - 한국과학기술원 : 전기및전자공학전공,
서지주기 참고문헌 : p. 45-49
주제 독립 요소 해석
선택적 주의 집중
잡음하 음성 인식
Independent component analysis
Selective attention
Noisy speech recognition
QR CODE qr code