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Published in:
2006 | OriginalPaper | Chapter
A Study of Knowledge-Based Features for Obstruent Detection and Classification in Continuous Mandarin Speech
Authors : Kuang-Ting Sung, Hsiao-Chuan Wang
Published in: Chinese Spoken Language Processing
Publisher: Springer Berlin Heidelberg
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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 of obstruent classification is about 80%. The proposed approach based on the feature distribution is simple and effective. It could be a very promising method for improving the phone detection in continuous speech recognition.