A Study on Detection and Recognition of Obstruents in Continuous Mandarin Speech

• Main Authors: Sung, Kuang-Ting, 宋光婷
• Other Authors: Wang, Hsiao-Chuan
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/84701195596019021219

碩士 === 國立清華大學 === 電機工程學系 === 94 === A study on acoustic-phonetic features for the obstruent detection and classification based on the knowledge of Mandarin speech is proposed. Seneff auditory model is used as the front-end processor for extracting acoustic-phonetic features. These features are rich in their information content in a hierarchical decision process to detect and classify the Mandarin obstruents. The preliminary experiments showed that accuracy of obstruent detection is about 84%. An algorithm based on the information of feature distribution is applied to further classify the obstruents into stops, fricatives, and affricates. The average accuracy is about 80%. The proposed approach based on the feature distribution is simple and effective. It could be a very promising method for searching acoustic-phonetic features for the phone recognition in continuous speech recognition.