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AuthorZayyan, Ayman A.
AuthorElmahdy, Mohamed
AuthorHusni, Husniza Binti
AuthorYousf, Shahrul Azmi
Available date2021-09-01T10:02:46Z
Publication Date2016
Publication NameProceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA
ResourceScopus
URIhttp://dx.doi.org/10.1109/AICCSA.2016.7945665
URIhttp://hdl.handle.net/10576/22397
AbstractIn this paper, the problem of missing diacritic marks in most of dialectal Arabic written resources is addressed. Our aim is to implement a scalable and extensible platform for automatically retrieving the diacritic marks for undiacritized dialectal Arabic texts. Different rule-based and statistical techniques are proposed. These include: morphological analyzer-based, maximum likelihood estimate, and statistical n-gram models. The proposed platform includes helper tools for text preprocessing and encoding conversion. Diacritization accuracy of each technique is evaluated in terms of Diacritic Error Rate (DER) and Word Error Rate (WER). The approach trains several n-gram models on different lexical units. A data pool of both Modern Standard Arabic (MSA) data along with Dialectal Arabic data was used to train the models. 2016 IEEE.
Languageen
PublisherIEEE Computer Society
SubjectText processing
Diacritization
Dialectal arabics
Maximum likelihood estimate
Modern standards
Morphological analyzer
Statistical techniques
Text preprocessing
Vowelization
Maximum likelihood estimation
TitleCrosslingual automatic diacritization for Egyptian Colloquial Dialect
TypeConference Paper
dc.accessType Abstract Only


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