GAVQ를 이용한 음성인식에 관한 연구

• 영문명: A study on speech recognition using GAVQ(genetic algorithms vector quantization)
• 발행기관: 강원대학교 산업기술연구소
• 저자명: 이상희(Lee Sang Hee) 이재곤(Lee Jae Kon) 정호균(Jeong Ho Kyoun) 김용연(Kim Yong Yun) 남재성(Nam Jae Sung)
• 간행물 정보: 『산업기술연구』vol.19, 1~8쪽, 전체 8쪽
• 주제분류: 공학 > 공학일반
• 파일형태: PDF
• 발행일자: 1999.09.30

영문 초록

In this paper, we proposed a modofied genetic algorithm to minimize misclassification rate for determining the codebook. Genetic algorithms are adaptive methods which may be used solve search and optimization problems based on the genetic processes of biological organisms. But they generally require a large amount of computation efforts. GAVQ can choose the optimal individuals by genetic operators. The position of individuals are optimized to improve the recognition rate. The technical properties of this study is that prevents us from the local minimum problem, which is not avoidable by conventional VQ algorithms. We compared the simulation result with Matlab using phoneme data. The simulation results show that the recognition rate from GAVQ is improved by comparing the conventional VQ algorithms.

목차

Abstract

1. 서론

2. 음성인식 시스템의 개요

3. 유전자 알고리즘을 이용한 벡터 양자화

4. 음소 인식 실험

5. 결론

참고문헌

키워드

유전자 알고리즘 벡터 양자화 코드북 genetic algorithm vector quantization codebook