morphological, syntactic and diacritics rules for automatic diacritization of arabic sentences

Clicks: 198
ID: 213443
2017
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #13 of 25 articles by views in journal of heritage tourism

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
The diacritical marks of Arabic language are characters other than letters and are in the majority of cases absent from Arab writings. This paper presents a hybrid system for automatic diacritization of Arabic sentences combining linguistic rules and statistical treatments. The used approach is based on four stages. The first phase consists of a morphological analysis using the second version of the morphological analyzer Alkhalil Morpho Sys. Morphosyntactic outputs from this step are used in the second phase to eliminate invalid word transitions according to the syntactic rules. Then, the system used in the third stage is a discrete hidden Markov model and Viterbi algorithm to determine the most probable diacritized sentence. The unseen transitions in the training corpus are processed using smoothing techniques. Finally, the last step deals with words not analyzed by Alkhalil analyzer, for which we use statistical treatments based on the letters. The word error rate of our system is around 2.58% if we ignore the diacritic of the last letter of the word and around 6.28% when this diacritic is taken into account.
Reference Key
chennoufi2017journalmorphological, Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Amine Chennoufi;Azzeddine Mazroui
Journal journal of heritage tourism
Year 2017
DOI
10.1016/j.jksuci.2016.06.004
URL
http://www.sciencedirect.com/science/article/pii/S1319157816300428
Keywords
arabic language computer science

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.