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Towards Resolving Morphological Ambiguity in Arabic Intelligent Language Tutoring Framework

Towards Resolving Morphological Ambiguity in Arabic Intelligent Language Tutoring Framework. Khaled Shaalan Doaa Samy Marwa Magdy. Introduction . Arabic Morphological Ambiguity Problem The Proposed Disambiguation System Evaluation & Results Conclusions. Outlines. Introduction

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Towards Resolving Morphological Ambiguity in Arabic Intelligent Language Tutoring Framework

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  1. Towards Resolving Morphological Ambiguity in ArabicIntelligent Language Tutoring Framework KhaledShaalan DoaaSamy MarwaMagdy

  2. Introduction. Arabic Morphological Ambiguity Problem The Proposed Disambiguation System Evaluation & Results Conclusions Outlines

  3. Introduction Arabic Morphological Ambiguity Problem The Proposed Disambiguation System Evaluation & Results Conclusions Outlines

  4. Introduction curriculum sequence Adaptive navigation Intelligent Language Tutoring System adaptive presentation • A computer-based educational system that allows simulation of a human tutor. • its objective is to enhance teaching and learning of foreign languages. error remediation Intelligent feedback to student solutions

  5. Lack of resources, such as Learner corpus for Arabic language Lack of tools dealing with ill-formed input In ILTS, relaxing the constraints of the language to analyze learner’s answer results in handling more interpretations than systems designed for only well-formed input Main Challenges

  6. Main Challenges (cont‘d) Use techniques, such as constraints relaxation Analyzes قالت (said) In well formed systems: - 3rd female sg past verb • In ILTS: • 3rd person female sg • 1st person sg past verb • 2nd person male sg past verb • 2nd person female sg past verb Intelligent Language Tutoring System Erroneous Learner Answer More Interpretation

  7. Introduction Arabic Morphological Ambiguity Problem The Proposed Disambiguation System Evaluation & Results Conclusions Outlines

  8. Arabic language is one of the Semitic languages that is defined as a diacritizedlanguage. Unfortunately, diacritics are rarely used in current Arabic writing conventions. So two or more words in Arabic are homographic Arabic Morphological Ambiguity

  9. Homographic Example

  10. Factors of Arabic Ambiguity For example, the word أسد can be interpreted as أسد (lion) or أسٌدً (I-Block). For example, the deletion of the letter (و) in taking the present (imperfect) tense of the trilateral root و-ع-د /w-E-d/, it appears in written texts as يعد (promise). For example, the perfect verb suffix تcan indicate either: 1) first person singular, 2) second person singular masculine, 3) second person singular feminine, or 4) third person singular feminine. For example, the فعل /faEala/ and فعًل /faE~ala/. Main Factors Ambiguity of Undiacritized verb Arabic patterns Orthographic alteration operations such as deletion Some verb prefixes and suffixes can be homographic Prefixes and suffixes can produce a form homographic with another word class

  11. Introduction Arabic Morphological Ambiguity Problem The Proposed Disambiguation System Evaluation & Results Conclusions Outlines

  12. Affix Error Representation: Added final letter قال+ ت Feature Value و Answer أقول Feature Value Root ق-و-ل Lexical Category verb Stem قال Pattern فعل Prefix ‘’ Verb Type hollow Stem Error Representation: Added middle letter ق ل Suffix ت Prefix أ قالتو الحق دائما (I always said the truth) Lexical Category verb ا Verb Type hollow Suffix ‘’ Pattern فعل Tense imperfect Tense perfect Voice active Voice active Mood indicative Object Features ‘’ Subject Features 1st sg Subject Features Object Features 1st sg ‘’ The Proposed System Arabic ILTS Possible Word Analyses • Verb tense error • Verb conjugation • Vowel letters Question: Build a sentence using the following roots: ق-و-ل، ح-ق، د-و-م /q-w-l, H-q, d-w-m/ The question goal is: conjugation hollow verb in imperfect tense active voice Word Analyzer Module Disambiguation Module • Incorrect use of perfect verb instead of imperfect Item banking Selected Word Analysis Learner Answer Feedback Message Error Type Error Classification Module Tutoring Module

  13. Disambguation Module PrioritizedConditions Affix Collection Multiple Analyses Pattern Collection Selected Analysis No Action Multiple Analyses

  14. Prioritized Conditions Yes Select Passive Analysis The question goal is to test passive voice No Select Active Analysis Item banking Multiple Analyses

  15. Prioritized Conditions Yes Select Imperative Verb Analysis The question goal is to test imperative tense No Select perfect or imperfect verb Analysis Item banking Multiple Analyses

  16. Example If the learner writes the following sentence: تباع جدتي الارز (My-grandmother sells the-rice ) The system produces two analyses: Third person singular feminine imperfect verb in the active voice with converted middle letter Third person singular feminine imperfect verb in the passive voice

  17. Disambguation Module PrioritizedConditions Affix Collection Multiple Analyses Pattern Collection Selected Analysis No Action Multiple Analyses

  18. Example If the learner writes the following sentence: محمد تورطت في جريمة قتل (Mohamed was-involved in murder crime) The system produces four analyses: First person singular perfect verb in the active voice Second personsingular masculine perfectverb in the active voice Singularperfectverbconjugation in the active voice Second person singular feminine perfect verb in the active voice Third person singular feminine perfect verb in the active voice

  19. Disambguation Module PrioritizedConditions Affix Collection Multiple Analyses Pattern Collection Selected Analysis No Action Multiple Analyses

  20. Example If the learner writes the following sentence: جدي وجدتي نقلوا الي بيت جديد (my-grandfather and my-grandmother moved to a new house) The system produces two analyses: Third person masculine plural perfect verb in the active voice following the pattern 'فعل'. Third person masculine plural perfect verb in the active voice instead of dual Third person masculine plural perfect verb in the active voice following the pattern 'فعًل'.

  21. Introduction. Arabic Morphological Ambiguity Problem. The Proposed Disambiguation System. Evaluation & Results Conclusions Outlines

  22. Evaluations & Results Evaluation & Results • A real test set that consists of 116 real Arabic sentences is collected • The system successfully solved 60% of the cases

  23. Evaluation Problems Classification • For example, the erroneous word أجوب: • the imperfect verb أجيب />u-jiyb/ (I-answer), • 2) or imperfect verb أجوب />a-juwb/ (I-explore). Problems For example, the word تناول; 1) the noun تناول /tanAwul/ (dealing with/ eating), 2) the perfect verb تناول /tanAwala/ (he/it-dealt with/ ate), or 3) the imperfect verb تناول /tu-nAwil/ (hand over/ deliver). Orthographic match between un-diacritized forms Additional- orthographic matches as a result of relaxing a constraint

  24. Introduction Arabic Morphological Ambiguity Problem The Proposed Disambiguation System Evaluation & Results Conclusions Outlines

  25. The ambiguity problem presents a challenge to ILTS The preferred method in ILTS for disambiguating multiple readings should consider the likelihood of an error and the difficulty of concepts If a large tagged learner corpus exist then the ambiguity problem can be resolved by considering the likelihood of errors Conclusions

  26. Thank you

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