Using the Method of Weighted K-NN to Recognize Isolated Word for Speaker-Dependent System

• Main Authors: Hui-Chun Li, 李蕙珺
• Other Authors: 李宗寶
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/37015908315289027052

碩士 === 國立中興大學 === 應用數學系所 === 97 === This paper discuss the speech recognition of 337 isolated mandarin words from the speaker-dependent, and we choose 200 isolated mandarin words to speech recognition. The recognition method we used in this paper is the weighted of k-th nearest neighbor (WK-NN), it’s start from record our speech database with 337 isolated mandarin words ten times, and random select three times as the testing database, others become training database. After record speech database, we focus speech database on the pre-processing, then through the linear prediction coding、the cepstrum coding, and picking up the speech feature. In order to make the speech recognition system become stable and to be rapid, we expand and condense to fixed the frame number for the isolated mandarin words. The experimental result is used to proceed the speaker-dependent recognition system. The rate of recoginition obtains 80.83% under 200 isolated mandarin words. Eventually, some suggestions are given to improve the rate of recognition for the future work.