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7 Testing and evaluation This chapter presents the results of the evaluation. Evaluation of MT software is nec- essary in order to improve system performance and analyse potential problems and, of course, its accuracy and effectiveness. In the evaluation session we consider many different aspects of the MT system including quality of translation, time for translation ability to add a new word in the lexicon of the system and resource utilization. 7.1 Evaluation of MT systems The evaluation of MT systems is a difficult task. This is not only because many different metrics are involved, but also because translation is itself difficult (Laoudi et al. 2004). The first important aspect for a potential test is to determine the translational capability. Therefore, we need to draw up a complete overview of the translational process, in all its different aspects. A good translation has to effectively capture the meaning. This involves establishing the size of the translation task, is it machine legible and if so, according 100
7.2. SENTENCE TESTS to which standards? Current general function MT systems can not translate all texts consistently. Output can have very poor quality. It is important to mention that the ‘subsequent editing required’ increases as translation quality gets poorer (Turian et al. 2003). Given the limited lexicon implemented in this work so far, we evaluate the effectiveness and accuracy of UniArab by comparison. We create variants of Arabic sentences that represent all possible structures of the sentences that UniArab can translate. We then compare between human-translated and machine-translated versions. 7.2 Sentence tests We have sentences (for actual test examples see Appendix C) in Arabic and their equiv- alent translations in English. We have covered a representative broad selection of verbs across intransitive, transitive and ditransitive constructions in simplex sentences in ac- tive voice. Complex sentences are beyond the thesis scope. However, we do address copula-like nominative clauses in Arabic. We tested UniArab in more than one way. We tested single sentences and multiple sentences. UniArab easily deals with more than one sentence as input and its output matches. We entered random sentences together in one input or as individual sentences. 101
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A generic framework for Arabic to E
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sentence and its linking algorithm
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Declaration I herby certify that th
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advices, but also academically and
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CONTENTS 2.3.1.2 Indefinite nouns .
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CONTENTS 4.4.1 Non-Roman alphabet s
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CONTENTS 7.2.8 Limitation of UniAra
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LIST OF FIGURES 4.4 Difference betw
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List of Tables 2.1 Dual: merely add
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LIST OF TABLES 5.9 Test strategy: p
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1 Introduction The following paragr
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high-quality translation technology
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1.3. TECHNOLOGIES ditransitive). Th
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1.4. THESIS ORGANIZATION 2009b). Ch
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2.1. CHARACTERISTICS OF THE ARABIC
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2.2 Characteristics of Arabic words
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2.2. CHARACTERISTICS OF ARABIC WORD
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2.3. PART OF SPEECH INVENTORY OF TH
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2.3.4 Verbs 2.3. PART OF SPEECH INV
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2.3.4.2 Aspect 2.3. PART OF SPEECH
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2.3. PART OF SPEECH INVENTORY OF TH
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2.4.1.1 Verb and noun 2.4. SENTENCE
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Table 2.27: verb(V), subject(S) and
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3 Role and Reference Grammar (RRG)
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3.1. ROLE AND REFERENCE GRAMMAR LIN
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3.2. FORMAL REPRESENTATION OF LAYER
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3.3. NOUN PHRASE STRUCTURE appropri
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3.4. LEXICAL REPRESENTATIONS FOR VE
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3.5. WHY WE USE RRG AS THE LINGUIST
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3.5. WHY WE USE RRG AS THE LINGUIST
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3.6. SUMMARY there will be more com
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4.1. ADVANTAGES OF MACHINE TRANSLAT
Page 69 and 70: 4.2.3 Lexical databases 4.2. COMPUT
Page 71 and 72: 4.3.2 Direct translation 4.3. BASIC
Page 73 and 74: 4.3. BASIC MACHINE TRANSLATION STRA
Page 75 and 76: would also be needed for an interli
Page 77 and 78: 4.4.1 Non-Roman alphabet scripts 4.
Page 79 and 80: Figure 4.5: NP rule (NP -> det n pp
Page 81 and 82: 4.5. CHALLENGES OF ARABIC TO ENGLIS
Page 83 and 84: Figure 4.7: Direct MT system 4.6.2
Page 85 and 86: 4.7 Summary Figure 4.9: Structure t
Page 87 and 88: 5 Design of Arabic to English machi
Page 89 and 90: 5.2. DESIGNING AN XML LEXICON ARCHI
Page 95 and 96: 5.3. DESIGN OF TEST STRATEGY Table
Page 97 and 98: 5.4. DESIGN OF EVALUATION CRITERIA
Page 99 and 100: 6 UniArab: a proof-of-concept Arabi
Page 101 and 102: 6.1. CONCEPTUAL STRUCTURE OF THE UN
Page 107 and 108: 6.2. UNIARAB: LEXICAL REPRESENTATIO
Page 113 and 114: 6.3. UNIARAB: GENERATION which mean
Page 115 and 116: Figure 6.11: UniArab’s GUI 1 6.4.
Page 117 and 118: 6.4.1 Lexicon interface Figure 6.13
Page 119: 6.6 Summary 6.6. SUMMARY We present
Page 123 and 124: Table 7.2: Test : Verb-subject; agr
Page 125 and 126: Figure 7.4: Verb-subject agreement
Page 127 and 128: Table 7.5: Test : gender-ambiguous
Page 129 and 130: Table 7.7: Test : Verb ‘to be’
Page 131 and 132: Table 7.9: Test : Verb ‘to have
Page 133 and 134: 7.2. SENTENCE TESTS Table 7.11: Tes
Page 135 and 136: 7.2.6 Pro-drop Arabic Table 7.13: T
Page 137 and 138: Table 7.15: Test : Intransitive 2 A
Page 139 and 140: 7.2.7.3 Ditransitive Table 7.17: Te
Page 141 and 142: Table 7.19: Test : Ditransitive wit
Page 143 and 144: 7.2. SENTENCE TESTS In a case where
Page 145 and 146: 7.3 System evaluation 7.3. SYSTEM E
Page 147 and 148: 7.3. SYSTEM EVALUATION search engin
Page 149 and 150: Now is not the end. It is not the b
Page 151 and 152: 8.1. THESIS SUMMARY and so we hope
Page 153 and 154: and proving the suitability of the
Page 155 and 156: References Abn-Aqeal, 2007. sharah
Page 157 and 158: REFERENCES Salem, Y., Hensman, A.,
Page 159 and 160: Appendix 139
Page 161 and 162: • Yasser Salem and Brian Nolan. 2
Page 163 and 164: Arabic Letter and Phonetic Value Le
Page 165 and 166: C List of translatable sentences I
Page 167 and 168: she is an engineer. Zaid loves Fati
Page 169 and 170: Jack is eating with the spoon.
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Ayah tore the page. ֓āyh
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Eman saw Sarah. r֓at ֓iymā
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Carl is brushing his hair. ym
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I want a book. ֓aryd ktāb
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Omar gave the book to Khalid.
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D Verbs in lexicon Verbs in Arabic
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Arabic Example Logical Structure
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Arabic Example Logical Structure
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Arabic ys. rs. r Example the wheel
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Arabic ֓adrs Example I am teach
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Package: Name of Class Class Summar
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