An acoustic-phonetic approach in automatic Arabic speech recognition

مرکز و کتابخانه مطالعات اسلامی به زبان های اروپایی

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" An acoustic-phonetic approach in automatic Arabic speech recognition "
Al-Zabibi, Marwan

Document Type	:	Latin Dissertation
Record Number	:	827981
Doc. No	:	TLets281043
Main Entry	:	Al-Zabibi, Marwan
Title & Author	:	An acoustic-phonetic approach in automatic Arabic speech recognition\ Al-Zabibi, Marwan
College	:	Loughborough University
Date	:	1990
student score	:	1990
Degree	:	Thesis (Ph.D.)
Abstract	:	In a large vocabulary speech recognition system the broad phonetic classification technique is used instead of detailed phonetic analysis to overcome the variability in the acoustic realisation of utterances. The broad phonetic description of a word is used as a means of lexical access, where the lexicon is structured into sets of words sharing the same broad phonetic labelling. This approach has been applied to a large vocabulary isolated word Arabic speech recognition system. Statistical studies have been carried out on 10,000 Arabic words (converted to phonemic form) involving different combinations of broad phonetic classes. Some particular features of the Arabic language have been exploited. The results show that vowels represent about 43% of the total number of phonemes. They also show that about 38% of the words can uniquely be represented at this level by using eight broad phonetic classes. When introducing detailed vowel identification the percentage of uniquely specified words rises to 83%. These results suggest that a fully detailed phonetic analysis of the speech signal is perhaps unnecessary. In the adopted word recognition model, the consonants are classified into four broad phonetic classes, while the vowels are described by their phonemic form. A set of 100 words uttered by several speakers has been used to test the performance of the implemented approach. In the implemented recognition model, three procedures have been developed, namely voiced-unvoiced-silence segmentation, vowel detection and identification, and automatic spectral transition detection between phonemes within a word. The accuracy of both the V-UV-S and vowel recognition procedures is almost perfect. A broad phonetic segmentation procedure has been implemented, which exploits information from the above mentioned three procedures. Simple phonological constraints have been used to improve the accuracy of the segmentation process. The resultant sequence of labels are used for lexical access to retrieve the word or a small set of words sharing the same broad phonetic labelling. For the case of having more than one word-candidates, a verification procedure is used to choose the most likely one.
Subject	:	Linguistics ; Speech recognition
Added Entry	:	Loughborough University