Using the Method of Multiple Common Vector and Dynamic Time Warping to Recognize Isolated Mandarin Word for Speaker-Dependent System

• Main Authors: Tzu-Chieh Lin, 林子傑
• Other Authors: 李宗寶
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/62944309029935884638

碩士 === 國立中興大學 === 應用數學系所 === 96 === This paper is to discuss the speech recognition of 50 isolated mandarin words. First, we use the relationship between principal component analysis and common vector to construct the speech model. Then we will take into account the time factor and attempt to join the dynamic time warping to improve the rate of recognition. Including dynamic time warping, we also consider the other four experimental factors in this paper: "the number of frame", "the number of cluster", "the number of eigenvector", and "speech feature extraction". We hope to find out which circumstances for the recognition of 50 words would be the best. And the maximum rate of recognition attains 97.33 % on the 50 words.