Abstract
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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Sung, KT., Wang, HC. (2006). A Study of Knowledge-Based Features for Obstruent Detection and Classification in Continuous Mandarin Speech. In: Huo, Q., Ma, B., Chng, ES., Li, H. (eds) Chinese Spoken Language Processing. ISCSLP 2006. Lecture Notes in Computer Science(), vol 4274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11939993_14
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DOI: https://doi.org/10.1007/11939993_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49665-6
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