Title:
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AN ALGORITHM ANALYZING PHONEME-GRAPHEME AWARENESS THROUGH THE BREAKDOWN OF WORDS |
Author(s):
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Zachariah Clifford Micallef, Mark Bugeja, Dunstan Briffa and Dylan Seychell |
ISBN:
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978-989-8704-14-6 |
Editors:
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Piet Kommers, Boyan Bontchev and Pedro IsaĆas |
Year:
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2020 |
Edition:
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Single |
Keywords:
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Accessibility, Dyslexic, Analyzing Spelling, Machine Learning, Phonological Awareness, Diagnosing |
Type:
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Short |
First Page:
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155 |
Last Page:
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159 |
Language:
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English |
Cover:
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Full Contents:
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click to dowload
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Paper Abstract:
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Phoneme awareness and orthography are core language skills, in this paper the relationship between both is monitored. There are two main parts to this experiment. The first is a group of algorithms that enable the measures of the described relationship and the second uses the previous measurements to solve a classification problem that related to a real-world problem. Participants are asked to spell a list of words by audio and divide each word into groups of letters that describe the shortest units of sound. This is done so that the correlation between how a person hears a word and how they write it can be observed. Once the data is collected the former part is used to deduct a score. The latter part of the experiment is done to prove the effectiveness of the scoring. Dyslexia is a clinical issue that is known to affect phonological awareness that relates to poor orthography. For this experiment, participants with this profile were asked to participate. Using the score obtained from the data, a classification model is trained in an attempt to classify dyslexic and non-dyslexic participants. This will be used to gauge the effectiveness of the scoring. The experiment has already been proven to work with a limited amount of data. |
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