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Syllable Identification

Zamin, Norshuhani (2004) Syllable Identification. Masters thesis, Universiti Teknologi Petronas.

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Abstract

Syllabification is part of the linguistic problems and developing computer software to predict the syllable boundaries is a challenging task. In practice, it is easier to determine the syllable boundaries manually especially in a syllabic spelling system with the fact that we know the linguistic element of the language. Identifying syllable boundaries for English is a daunting process because English is an alphabetic spelling system. To write software, it is traditionally assumed that various sources of linguistic knowledge should be incorporated in order to convert words into their syllable structure with reasonable accuracy. The linguistic knowledge is important to define the graphotactic and phonetic rules. The purpose of this project has been to investigate the problem in English syllabification and to represent 2 different approaches to automatic detection of syllable boundaries. The first approach syllabifies a text from its grapheme or symbol while the second approach syllabifies a text from its sound. It was found that, many existing research on syllabification adopted the second approach. Although different researchers propose different knowledge structure but most of them used the typical architecture for grapheme-to-phoneme conversion while to go from text to grapheme or symbol is a new technique. In this project, I demonstrate the use of hand-written rules for English syllabification and knowledge structures trained on both approaches and compare the performance and accuracy of these approaches. The evaluation shows that going from text to symbol is easier and it performs better on finding the syllable boundaries than going from text to sound. Recommendations for future projects of this nature are made. Keywords Syllable; syllabification; maximum onset principle; phonotactic; graphotactic; diagraph rule; silent rules; orthography; syllabic consonant; consonant clusters; segmentation; constraints.

Item Type: Thesis (Masters)
Academic Subject : Academic Department - Information Communication Technology
Subject: T Technology > T Technology (General)
Divisions: Sciences and Information Technology > Computer and Information Sciences
Depositing User: Users 2053 not found.
Date Deposited: 30 Sep 2013 16:55
Last Modified: 25 Jan 2017 09:46
URI: http://utpedia.utp.edu.my/id/eprint/7854

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