잡음환경에 강인한 화자확인에 관한 연구

• 영문명: Robust Speaker Verification in Noisy Environments
• 발행기관: 한국산업기술융합학회(구. 산업기술교육훈련학회)
• 저자명: 위진우(Jinwoo Wee)
• 간행물 정보: 『산업기술연구논문지』산업기술연구논문지 제24권 4호, 53~60쪽, 전체 8쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2019.12.30

영문 초록

The first proposed speaker verification method for the preprocessing part is the linear predictive coding (LPC) cepstrum weighting function that modifies the existing one. Simulation results show that the average speaker verification rate is improved by 17.7% using the proposed end-point detection algorithm using LPC residue, and it is improved by 37% using the proposed noise cancelling and microphone property compensation algorithm. The proposed weighting function for discriminating inter-speaker variations also improves the average speaker verification rate by 6.6% (FR). The second proposed speaker verification method for the speaker verification part is a modified clustering algorithm. In this study, a nonlinear clustering algorithm is used. The proposed method increased the speaker verification rate by 1.0% (FR). The following are proposed in the study: a method for reducing the training utterance number, a method using the personal vector quantization code book for improving the imposter acceptance rate, the observation symbol probability smoothing method by probability weights for improving the DHMM performance, and the speaker model adaptation method for adapting the voice variance. The two verification methods mentioned above are applied to the general DHMM. The results showed a performance enhancement of about 1.1% in FA and 41.7% in FR.

목차

Ⅰ. 서 론

Ⅱ. 잡음환경에 강인한 제안된 화자확인 시스템

Ⅲ. 실험결과 및 고찰

Ⅳ. 결 론

키워드

화자확인 켑스트럼 이산은닉 마르코프모델 끝점추출 잔여 선형예측계수 Speaker Verificaton Cepstrum DHMM End-Point Detection LPC Residue