대한음성학회:학술대회논문집 (Proceedings of the KSPS conference)
- 대한음성학회 2007년도 한국음성과학회 공동학술대회 발표논문집
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- Pages.319-322
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- 2007
주성분분석과 선형판별분석의 장점을 이용한 강인한 화자식별
Robust Speaker Identification Exploiting the Advantages of PCA and LDA
- Kim, Min-Seok (School of Computer Science, University of Seoul) ;
- Yu, Ha-Jin (School of Computer Science, University of Seoul) ;
- Kim, Sung-Joo (School of Computer Science, University of Seoul)
- 발행 : 2007.05.18
초록
The goal of our research is to build a textindependent speaker identification system that can be used in mobile devices without any additional adaptation process. In this paper, we show that exploiting the advantages of both PCA(Principle Component Analysis) and LDA(Linear Discriminant Analysis) can increase the performance in the situation. The proposed method reduced the relative recognition error by 13.5%
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