Fuzzy petri nets as a classification method for automatic speech intelligibility detection of children with speech impairments / Fadhilah Rosdi

The inability to speak fluently degrades the quality of life of many individuals. Early intervention from childhood can reduce disfluency of speech among adults. Traditionally, disfluency of speech among children is diagnosed based on speech intelligibility assessment by speech and language patholog...

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Main Author: Fadhilah, Rosdi
Format: Thesis
Published: 2016
Subjects:
Online Access:http://studentsrepo.um.edu.my/6828/
http://studentsrepo.um.edu.my/6828/4/fadhilah.pdf
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author Fadhilah, Rosdi
author_facet Fadhilah, Rosdi
author_sort Fadhilah, Rosdi
building UM Research Repository
collection Online Access
description The inability to speak fluently degrades the quality of life of many individuals. Early intervention from childhood can reduce disfluency of speech among adults. Traditionally, disfluency of speech among children is diagnosed based on speech intelligibility assessment by speech and language pathologists, which can be expensive and time consuming. Hence, numerous attempts were made to automate the speech intelligibility detection. While current detectors use statistical methods to discriminate unintelligible speech by calculating the posterior probability scores for each articulatory feature class, the major drawback is that the results are most likely to be based on training and input data, leading to inconsistencies in discriminating speech sounds. As such, the performance of detectors is below that of humans. To overcome this limitation, a new classification method based on Fuzzy Petri Net (FPN) is proposed to improve the classification accuracy. FPN was proposed as it has greater knowledge representation ability to reason using uncertain or ambiguous information. In this research, the speech features of Malay impaired children’s speech are analysed for the identification of the significant speech features in the impaired speech which are related to the intelligibility deficits. This research also presents how the intelligibility classes can be detected by FPN. The results showed that FPN is more reliable in discriminating speech sounds than the baseline classifiers with improvements in the classification accuracy, precision and recall.
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spelling um-68282020-01-18T02:57:54Z Fuzzy petri nets as a classification method for automatic speech intelligibility detection of children with speech impairments / Fadhilah Rosdi Fadhilah, Rosdi QA75 Electronic computers. Computer science The inability to speak fluently degrades the quality of life of many individuals. Early intervention from childhood can reduce disfluency of speech among adults. Traditionally, disfluency of speech among children is diagnosed based on speech intelligibility assessment by speech and language pathologists, which can be expensive and time consuming. Hence, numerous attempts were made to automate the speech intelligibility detection. While current detectors use statistical methods to discriminate unintelligible speech by calculating the posterior probability scores for each articulatory feature class, the major drawback is that the results are most likely to be based on training and input data, leading to inconsistencies in discriminating speech sounds. As such, the performance of detectors is below that of humans. To overcome this limitation, a new classification method based on Fuzzy Petri Net (FPN) is proposed to improve the classification accuracy. FPN was proposed as it has greater knowledge representation ability to reason using uncertain or ambiguous information. In this research, the speech features of Malay impaired children’s speech are analysed for the identification of the significant speech features in the impaired speech which are related to the intelligibility deficits. This research also presents how the intelligibility classes can be detected by FPN. The results showed that FPN is more reliable in discriminating speech sounds than the baseline classifiers with improvements in the classification accuracy, precision and recall. 2016-09 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/6828/4/fadhilah.pdf Fadhilah, Rosdi (2016) Fuzzy petri nets as a classification method for automatic speech intelligibility detection of children with speech impairments / Fadhilah Rosdi. PhD thesis, University of Malaya. http://studentsrepo.um.edu.my/6828/
spellingShingle QA75 Electronic computers. Computer science
Fadhilah, Rosdi
Fuzzy petri nets as a classification method for automatic speech intelligibility detection of children with speech impairments / Fadhilah Rosdi
title Fuzzy petri nets as a classification method for automatic speech intelligibility detection of children with speech impairments / Fadhilah Rosdi
title_full Fuzzy petri nets as a classification method for automatic speech intelligibility detection of children with speech impairments / Fadhilah Rosdi
title_fullStr Fuzzy petri nets as a classification method for automatic speech intelligibility detection of children with speech impairments / Fadhilah Rosdi
title_full_unstemmed Fuzzy petri nets as a classification method for automatic speech intelligibility detection of children with speech impairments / Fadhilah Rosdi
title_short Fuzzy petri nets as a classification method for automatic speech intelligibility detection of children with speech impairments / Fadhilah Rosdi
title_sort fuzzy petri nets as a classification method for automatic speech intelligibility detection of children with speech impairments / fadhilah rosdi
topic QA75 Electronic computers. Computer science
url http://studentsrepo.um.edu.my/6828/
http://studentsrepo.um.edu.my/6828/4/fadhilah.pdf