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An acoustic-phonetic feature-based system for automatic phoneme recognition in continuous speech

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5 Author(s)
Ali, A.M.A. ; Dept. of Electr. Eng., Pennsylvania Univ., Philadelphia, PA, USA ; Van der Spiegel, J. ; Mueller, P. ; Haentjens, G.
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An acoustic-phonetic feature- and knowledge-based system for the automatic segmentation, broad categorization and fine phoneme recognition of continuous speech is described. The system uses an auditory-based front-end processing and incorporates new knowledge-based algorithms to automatically segment the speech into phoneme-like segments that are further categorized into 4 main categories: sonorants, stops, fricatives and silences. The final outputs from the system are 19 class phonemes which contain 7 stops, 6 fricatives, nasals and semivowels, 4 vowel classes and silences. The system was tested on continuous speech from 30 speakers having 7 different dialects from the TIMIT database which were not used in the design process. The results are 92% accuracy for the segmentation and categorization, 86% for the stop classification, 90% for the fricative classification, 75% for the nasal and semivowel extraction and 82% for the vowel recognition. These results compare favorably with previous phoneme classification results

Published in:

Circuits and Systems, 1999. ISCAS '99. Proceedings of the 1999 IEEE International Symposium on  (Volume:3 )

Date of Conference:

Jul 1999