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1
Challenges in Using an Example-Based MT System for a Transnational Digital Government Project
In: http://www.cs.cmu.edu/~violetta/EAMT2004_FINAL.pdf (2004)
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2
Developing Language Resources for a Transnational Digital Government System
In: http://www.lrec-conf.org/proceedings/lrec2004/pdf/713.pdf (2004)
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3
Developing Language Resources for Transnational Digital Government Systems
In: http://www.cs.cmu.edu/~violetta/LREC2004_FINAL.pdf (2004)
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4
A Computational Lexeme-Based Treatment of Arabic Morphology
In: http://www.elsnet.org/arabic2001/cavalli.pdf (2001)
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5
Challenges in Adapting an Interlingua for Bidirectional English-Italian Translation
In: http://www.lti.cs.cmu.edu/Research/Kant/PostScript/amta2000_italian.ps (2000)
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6
Arabic morphology generation using a concatenative strategy
In: http://libra.sfsu.edu/~vcs/NAACL_2000.pdf (2000)
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7
Arabic Morphology Generation Using a Concatenative Strategy
In: http://www.mt.cs.cmu.edu/Research/Kant/PDF/naacl_arabic.pdf (2000)
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8
Arabic Morphology Generation Using a Concatenative Strategy
In: http://acl.ldc.upenn.edu/A/A00/A00-2012.pdf (2000)
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9
Arabic Morphology Generation Using a Concatenative Strategy
In: http://www.mt.cs.cmu.edu/Research/Kant/PostScript/naacl_arabic.ps (2000)
Abstract: Arabic inflectional morphology requires infixation, prefixation and suffixation, giving rise to a large space of morphological variation. In this paper we describe an approach to reducing the complexity of Arabic morphology generation using discrimination trees and transformational rules. By decoupling the problem of stem changes from that of prefixes and suffixes, we gain a significant reduction in the number of rules required, as much as a factor of three for certain verb types. We focus on hollow verbs but discuss the wider applicability of the approach. Introduction Morphologically, Arabic is a non-concatenative language. The basic problem with generating Arabic verbal morphology is the large number of variants that must be generated. Verbal stems are based on triliteral or quadriliteral roots (3- or 4-radicals). Stems are formed by a derivational combination of a root morpheme and a vowel melody; the two are arranged according to canonical patterns. Roots ar.
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.35.5430
http://www.mt.cs.cmu.edu/Research/Kant/PostScript/naacl_arabic.ps
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10
The Arabic Noun System Generation 1
In: http://libra.sfsu.edu/~vcs/Manouba_2002.pdf
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11
IMORPHĒ: An Inheritance and Equivalence Based Morphology Description Compiler
In: http://www.cs.brandeis.edu/~marc/misc/proceedings/lrec-2006/pdf/409_pdf.pdf
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12
Challenges in Adapting an Interlingua for Bidirectional English-Italian Translation
In: http://www.cs.cmu.edu/~violetta/AMTA_2000.pdf
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13
IMORPHĒ: An Inheritance and Equivalence Based Morphology Description Compiler
In: http://www.cs.cmu.edu/~violetta/LREC2006.pdf
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14
Extensions to a Histogram-Based Student Modeling Approach to Facilitate Reading in Morphologically Complex Languages
In: http://papers.ldc.upenn.edu/AIED/StudentModelingApproach.pdf
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15
Published In
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16
Extensions to a Histogram-Based Student Modeling Approach to Facilitate Reading in Morphologically Complex Languages
In: http://www.cs.cmu.edu/~violetta/AIED2005_SMforLT_paper.pdf
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17
Developing ARET: An NLP-based Educational Tool Set for Arabic Reading Enhancement
In: http://aclweb.org/anthology-new/W/W12/W12-2015.pdf
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18
Developing ARET: An NLP-based Educational Tool Set for Arabic Reading Enhancement
In: http://papers.ldc.upenn.edu/NAACL2012/DevelopingARET.pdf
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19
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20
Arabic Morphology Generation Using a Concatenative Strategy
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