Challenges for Arabic Machine Translation /:
This book is the first volume that focuses on the specific challenges of machine translation with Arabic either as source or target language. It nicely fills a gap in the literature by covering approaches that belong to the three major paradigms of machine translation: Example-based, statistical and...
Gespeichert in:
1. Verfasser: | |
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Weitere Verfasser: | , , |
Format: | Elektronisch E-Book |
Sprache: | English Arabic |
Veröffentlicht: |
Amsterdam/Philadelphia :
John Benjamins Publishing Company,
2012.
|
Schriftenreihe: | Natural language processing.
|
Schlagworte: | |
Online-Zugang: | Volltext |
Zusammenfassung: | This book is the first volume that focuses on the specific challenges of machine translation with Arabic either as source or target language. It nicely fills a gap in the literature by covering approaches that belong to the three major paradigms of machine translation: Example-based, statistical and knowledge-based. It provides broad but rigorous coverage of the methods for incorporating linguistic knowledge into empirical MT. The book brings together original and extended contributions from a group of distinguished researchers from both academia and industry. |
Beschreibung: | 2. Related work. |
Beschreibung: | 1 online resource (165 pages) |
Bibliographie: | ReferencesArabic Preprocessing for Statistical Machine Translation; 1. Introduction; 2. Related Work; 3. Arabic Linguistic Issues; 3.1 Orthographic Ambiguity; 3.2 Clitics; 3.3 Adjustment Rules; 3.4 Templatic Inflections; 4. Preprocessing: Schemes and Techniques; 4.1 Preprocessing Techniques; 4.1.1 REGEX; 4.1.2 BAMA; 4.1.3 MADA; 4.2 Preprocessing Schemes; 4.3 Comparing Various Schemes; 5 Experiments; 5.1 Portage; 5.2 Experimental data; 5.3 Experimental Results; 5.4 Discussion; 5.5 Genre Variation; 5.6 Phrase Size; 6. Scheme Combination; 6.1 Oracle Experiment; 6.2 Rescoring-only Combination. |
ISBN: | 9789027273628 9027273626 9789027249951 9027249954 1283521547 9781283521543 9786613833990 6613833991 |
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245 | 1 | 0 | |a Challenges for Arabic Machine Translation / |c Abdelhadi Soudi. |
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505 | 0 | |a Challenges for Arabic Machine Translation; Editorial page; Title page; LCC data; Table of contents; Preface; Introduction; 1. Overview; 2. Challenges of Arabic machine translation; 3. Arabic linguistic resources; 4. Example-based machine translation; 5. Statistical machine translation; 6. Knowledge-based machine translation; 7. Arabic transliteration scheme; References; Linguistic resources for Arabic machine translation; 1. Introduction; 2. LDC's distribution model; 3. Arabic speech collections; 4. Arabic text collections; 4.1 Parallel text; 4.2 NIST resources. | |
505 | 8 | |a 5. Arabic morphological analyzer6. Arabic treebank and parallel English treebank; 7. Arabic-English word alignment; 8. Additional resources; References; Using morphology to improve Example-Based Machine Translation; 1. Introduction; 2. Example-Based Machine Translation: What is it and why use it?; 3. Adding morphology to EBMT for Arabic-to-English translation; 3.1 Generalization and morphological analysis in BAMA; 3.2 Phase 1: Focus on generalization and filtering; 3.2.1 Generalization; 3.2.2 Filtering; 3.2.3 Generalization and filtering are not enough. | |
505 | 8 | |a 3.3 Phase 2: Generalization, filtering and adaptation3.3.1 Generalization; 3.3.2 Filtering and adaptation; 3.3.3 Scoring; 3.3.4 Results; 4. Related work; 5. Summary and conclusions; References; Using semantic equivalents for Arabic-to-English example-based translation; 1. Introduction; 2. Related work; 3. System description; 3.1 Translation corpus; 3.2 Matching; 4. Noun experiment; 4.1 The noun thesaurus; 4.2 Using noun synonyms for translation; 4.3 Experimental results; 5. Verb experiment; 5.1 The verb thesaurus; 5.2 Using synonyms in translation; 5.3 Experimental results; 6. Conclusions. | |
504 | |a ReferencesArabic Preprocessing for Statistical Machine Translation; 1. Introduction; 2. Related Work; 3. Arabic Linguistic Issues; 3.1 Orthographic Ambiguity; 3.2 Clitics; 3.3 Adjustment Rules; 3.4 Templatic Inflections; 4. Preprocessing: Schemes and Techniques; 4.1 Preprocessing Techniques; 4.1.1 REGEX; 4.1.2 BAMA; 4.1.3 MADA; 4.2 Preprocessing Schemes; 4.3 Comparing Various Schemes; 5 Experiments; 5.1 Portage; 5.2 Experimental data; 5.3 Experimental Results; 5.4 Discussion; 5.5 Genre Variation; 5.6 Phrase Size; 6. Scheme Combination; 6.1 Oracle Experiment; 6.2 Rescoring-only Combination. | ||
505 | 8 | |a 6.3 Decoding-plus-Rescoring Combination6.4 Significance Test; 7. Conclusions; Acknowledgments; References; Preprocessing for English-to-Arabic statistical machine translation; 1. Introduction; 2. Morphological preprocessing for English-to-Arabic SMT; 2.1 Morphological segmentation of Arabic; 2.2 Recombination of segmented Arabic; 2.3 Experimental setup; 2.4 Experimental results; 3. Syntactic preprocessing for English-to-Arabic SMT; 3.1 Related work; 3.2 Reordering rules; 3.3 Experimental setup; 3.4 Results; 4. Summary; References; Lexical syntax for Arabic SMT; 1. Introduction. | |
500 | |a 2. Related work. | ||
520 | |a This book is the first volume that focuses on the specific challenges of machine translation with Arabic either as source or target language. It nicely fills a gap in the literature by covering approaches that belong to the three major paradigms of machine translation: Example-based, statistical and knowledge-based. It provides broad but rigorous coverage of the methods for incorporating linguistic knowledge into empirical MT. The book brings together original and extended contributions from a group of distinguished researchers from both academia and industry. | ||
546 | |a English. | ||
650 | 0 | |a Machine translating. | |
650 | 0 | |a English language |x Translating into Arabic. |0 http://id.loc.gov/authorities/subjects/sh2022004658 | |
650 | 0 | |a Arabic language |x Translating into English. |0 http://id.loc.gov/authorities/subjects/sh2022004540 | |
650 | 0 | |a Speech processing systems. | |
650 | 6 | |a Traduction automatique. | |
650 | 6 | |a Traitement automatique de la parole. | |
650 | 6 | |a Anglais (Langue) |x Traduction en arabe. | |
650 | 6 | |a Arabe (Langue) |x Traduction en anglais. | |
650 | 7 | |a FOREIGN LANGUAGE STUDY |x Arabic. |2 bisacsh | |
650 | 7 | |a Arabic language |x Translating into English |2 fast | |
650 | 7 | |a English language |x Translating into Arabic |2 fast | |
650 | 7 | |a Machine translating |2 fast | |
650 | 7 | |a Speech processing systems |2 fast | |
655 | 4 | |a Electronic book. | |
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author | Soudi, Abdelhadi |
author2 | Farghaly, Ali Neumann, Günter Zbib, Rabih |
author2_role | |
author2_variant | a f af g n gn r z rz |
author_GND | http://id.loc.gov/authorities/names/n2001041759 |
author_facet | Soudi, Abdelhadi Farghaly, Ali Neumann, Günter Zbib, Rabih |
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callnumber-label | P309 |
callnumber-raw | P309 .C43 2012 |
callnumber-search | P309 .C43 2012 |
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callnumber-subject | P - Philology and Linguistics |
collection | ZDB-4-EBA |
contents | Challenges for Arabic Machine Translation; Editorial page; Title page; LCC data; Table of contents; Preface; Introduction; 1. Overview; 2. Challenges of Arabic machine translation; 3. Arabic linguistic resources; 4. Example-based machine translation; 5. Statistical machine translation; 6. Knowledge-based machine translation; 7. Arabic transliteration scheme; References; Linguistic resources for Arabic machine translation; 1. Introduction; 2. LDC's distribution model; 3. Arabic speech collections; 4. Arabic text collections; 4.1 Parallel text; 4.2 NIST resources. 5. Arabic morphological analyzer6. Arabic treebank and parallel English treebank; 7. Arabic-English word alignment; 8. Additional resources; References; Using morphology to improve Example-Based Machine Translation; 1. Introduction; 2. Example-Based Machine Translation: What is it and why use it?; 3. Adding morphology to EBMT for Arabic-to-English translation; 3.1 Generalization and morphological analysis in BAMA; 3.2 Phase 1: Focus on generalization and filtering; 3.2.1 Generalization; 3.2.2 Filtering; 3.2.3 Generalization and filtering are not enough. 3.3 Phase 2: Generalization, filtering and adaptation3.3.1 Generalization; 3.3.2 Filtering and adaptation; 3.3.3 Scoring; 3.3.4 Results; 4. Related work; 5. Summary and conclusions; References; Using semantic equivalents for Arabic-to-English example-based translation; 1. Introduction; 2. Related work; 3. System description; 3.1 Translation corpus; 3.2 Matching; 4. Noun experiment; 4.1 The noun thesaurus; 4.2 Using noun synonyms for translation; 4.3 Experimental results; 5. Verb experiment; 5.1 The verb thesaurus; 5.2 Using synonyms in translation; 5.3 Experimental results; 6. Conclusions. 6.3 Decoding-plus-Rescoring Combination6.4 Significance Test; 7. Conclusions; Acknowledgments; References; Preprocessing for English-to-Arabic statistical machine translation; 1. Introduction; 2. Morphological preprocessing for English-to-Arabic SMT; 2.1 Morphological segmentation of Arabic; 2.2 Recombination of segmented Arabic; 2.3 Experimental setup; 2.4 Experimental results; 3. Syntactic preprocessing for English-to-Arabic SMT; 3.1 Related work; 3.2 Reordering rules; 3.3 Experimental setup; 3.4 Results; 4. Summary; References; Lexical syntax for Arabic SMT; 1. Introduction. |
ctrlnum | (OCoLC)804665162 |
dewey-full | 492.7/8020285635 |
dewey-hundreds | 400 - Language |
dewey-ones | 492 - Afro-Asiatic languages |
dewey-raw | 492.7/8020285635 |
dewey-search | 492.7/8020285635 |
dewey-sort | 3492.7 108020285635 |
dewey-tens | 490 - Other languages |
discipline | Außereuropäische Sprachen und Literaturen |
format | Electronic eBook |
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genre | Electronic book. |
genre_facet | Electronic book. |
id | ZDB-4-EBA-ocn804665162 |
illustrated | Not Illustrated |
indexdate | 2024-11-27T13:24:52Z |
institution | BVB |
isbn | 9789027273628 9027273626 9789027249951 9027249954 1283521547 9781283521543 9786613833990 6613833991 |
language | English Arabic |
lccn | 2012015208 |
oclc_num | 804665162 |
open_access_boolean | |
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owner_facet | MAIN DE-863 DE-BY-FWS |
physical | 1 online resource (165 pages) |
psigel | ZDB-4-EBA |
publishDate | 2012 |
publishDateSearch | 2012 |
publishDateSort | 2012 |
publisher | John Benjamins Publishing Company, |
record_format | marc |
series | Natural language processing. |
series2 | Natural Language Processing |
spelling | Soudi, Abdelhadi. Challenges for Arabic Machine Translation / Abdelhadi Soudi. Amsterdam/Philadelphia : John Benjamins Publishing Company, 2012. 1 online resource (165 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier text file rdaft Natural Language Processing Print version record. Challenges for Arabic Machine Translation; Editorial page; Title page; LCC data; Table of contents; Preface; Introduction; 1. Overview; 2. Challenges of Arabic machine translation; 3. Arabic linguistic resources; 4. Example-based machine translation; 5. Statistical machine translation; 6. Knowledge-based machine translation; 7. Arabic transliteration scheme; References; Linguistic resources for Arabic machine translation; 1. Introduction; 2. LDC's distribution model; 3. Arabic speech collections; 4. Arabic text collections; 4.1 Parallel text; 4.2 NIST resources. 5. Arabic morphological analyzer6. Arabic treebank and parallel English treebank; 7. Arabic-English word alignment; 8. Additional resources; References; Using morphology to improve Example-Based Machine Translation; 1. Introduction; 2. Example-Based Machine Translation: What is it and why use it?; 3. Adding morphology to EBMT for Arabic-to-English translation; 3.1 Generalization and morphological analysis in BAMA; 3.2 Phase 1: Focus on generalization and filtering; 3.2.1 Generalization; 3.2.2 Filtering; 3.2.3 Generalization and filtering are not enough. 3.3 Phase 2: Generalization, filtering and adaptation3.3.1 Generalization; 3.3.2 Filtering and adaptation; 3.3.3 Scoring; 3.3.4 Results; 4. Related work; 5. Summary and conclusions; References; Using semantic equivalents for Arabic-to-English example-based translation; 1. Introduction; 2. Related work; 3. System description; 3.1 Translation corpus; 3.2 Matching; 4. Noun experiment; 4.1 The noun thesaurus; 4.2 Using noun synonyms for translation; 4.3 Experimental results; 5. Verb experiment; 5.1 The verb thesaurus; 5.2 Using synonyms in translation; 5.3 Experimental results; 6. Conclusions. ReferencesArabic Preprocessing for Statistical Machine Translation; 1. Introduction; 2. Related Work; 3. Arabic Linguistic Issues; 3.1 Orthographic Ambiguity; 3.2 Clitics; 3.3 Adjustment Rules; 3.4 Templatic Inflections; 4. Preprocessing: Schemes and Techniques; 4.1 Preprocessing Techniques; 4.1.1 REGEX; 4.1.2 BAMA; 4.1.3 MADA; 4.2 Preprocessing Schemes; 4.3 Comparing Various Schemes; 5 Experiments; 5.1 Portage; 5.2 Experimental data; 5.3 Experimental Results; 5.4 Discussion; 5.5 Genre Variation; 5.6 Phrase Size; 6. Scheme Combination; 6.1 Oracle Experiment; 6.2 Rescoring-only Combination. 6.3 Decoding-plus-Rescoring Combination6.4 Significance Test; 7. Conclusions; Acknowledgments; References; Preprocessing for English-to-Arabic statistical machine translation; 1. Introduction; 2. Morphological preprocessing for English-to-Arabic SMT; 2.1 Morphological segmentation of Arabic; 2.2 Recombination of segmented Arabic; 2.3 Experimental setup; 2.4 Experimental results; 3. Syntactic preprocessing for English-to-Arabic SMT; 3.1 Related work; 3.2 Reordering rules; 3.3 Experimental setup; 3.4 Results; 4. Summary; References; Lexical syntax for Arabic SMT; 1. Introduction. 2. Related work. This book is the first volume that focuses on the specific challenges of machine translation with Arabic either as source or target language. It nicely fills a gap in the literature by covering approaches that belong to the three major paradigms of machine translation: Example-based, statistical and knowledge-based. It provides broad but rigorous coverage of the methods for incorporating linguistic knowledge into empirical MT. The book brings together original and extended contributions from a group of distinguished researchers from both academia and industry. English. Machine translating. English language Translating into Arabic. http://id.loc.gov/authorities/subjects/sh2022004658 Arabic language Translating into English. http://id.loc.gov/authorities/subjects/sh2022004540 Speech processing systems. Traduction automatique. Traitement automatique de la parole. Anglais (Langue) Traduction en arabe. Arabe (Langue) Traduction en anglais. FOREIGN LANGUAGE STUDY Arabic. bisacsh Arabic language Translating into English fast English language Translating into Arabic fast Machine translating fast Speech processing systems fast Electronic book. Farghaly, Ali. Neumann, Günter. http://id.loc.gov/authorities/names/n2001041759 Zbib, Rabih. has work: Challenges for Arabic machine translation (Text) https://id.oclc.org/worldcat/entity/E39PCFwc88cWHqTW9qDVG6ytVd https://id.oclc.org/worldcat/ontology/hasWork Print version: Soudi, Abdelhadi. Challenges for Arabic Machine Translation. Amsterdam/Philadelphia : John Benjamins Publishing Company, ©2012 9789027249951 Natural language processing. http://id.loc.gov/authorities/names/n91086627 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=471083 Volltext |
spellingShingle | Soudi, Abdelhadi Challenges for Arabic Machine Translation / Natural language processing. Challenges for Arabic Machine Translation; Editorial page; Title page; LCC data; Table of contents; Preface; Introduction; 1. Overview; 2. Challenges of Arabic machine translation; 3. Arabic linguistic resources; 4. Example-based machine translation; 5. Statistical machine translation; 6. Knowledge-based machine translation; 7. Arabic transliteration scheme; References; Linguistic resources for Arabic machine translation; 1. Introduction; 2. LDC's distribution model; 3. Arabic speech collections; 4. Arabic text collections; 4.1 Parallel text; 4.2 NIST resources. 5. Arabic morphological analyzer6. Arabic treebank and parallel English treebank; 7. Arabic-English word alignment; 8. Additional resources; References; Using morphology to improve Example-Based Machine Translation; 1. Introduction; 2. Example-Based Machine Translation: What is it and why use it?; 3. Adding morphology to EBMT for Arabic-to-English translation; 3.1 Generalization and morphological analysis in BAMA; 3.2 Phase 1: Focus on generalization and filtering; 3.2.1 Generalization; 3.2.2 Filtering; 3.2.3 Generalization and filtering are not enough. 3.3 Phase 2: Generalization, filtering and adaptation3.3.1 Generalization; 3.3.2 Filtering and adaptation; 3.3.3 Scoring; 3.3.4 Results; 4. Related work; 5. Summary and conclusions; References; Using semantic equivalents for Arabic-to-English example-based translation; 1. Introduction; 2. Related work; 3. System description; 3.1 Translation corpus; 3.2 Matching; 4. Noun experiment; 4.1 The noun thesaurus; 4.2 Using noun synonyms for translation; 4.3 Experimental results; 5. Verb experiment; 5.1 The verb thesaurus; 5.2 Using synonyms in translation; 5.3 Experimental results; 6. Conclusions. 6.3 Decoding-plus-Rescoring Combination6.4 Significance Test; 7. Conclusions; Acknowledgments; References; Preprocessing for English-to-Arabic statistical machine translation; 1. Introduction; 2. Morphological preprocessing for English-to-Arabic SMT; 2.1 Morphological segmentation of Arabic; 2.2 Recombination of segmented Arabic; 2.3 Experimental setup; 2.4 Experimental results; 3. Syntactic preprocessing for English-to-Arabic SMT; 3.1 Related work; 3.2 Reordering rules; 3.3 Experimental setup; 3.4 Results; 4. Summary; References; Lexical syntax for Arabic SMT; 1. Introduction. Machine translating. English language Translating into Arabic. http://id.loc.gov/authorities/subjects/sh2022004658 Arabic language Translating into English. http://id.loc.gov/authorities/subjects/sh2022004540 Speech processing systems. Traduction automatique. Traitement automatique de la parole. Anglais (Langue) Traduction en arabe. Arabe (Langue) Traduction en anglais. FOREIGN LANGUAGE STUDY Arabic. bisacsh Arabic language Translating into English fast English language Translating into Arabic fast Machine translating fast Speech processing systems fast |
subject_GND | http://id.loc.gov/authorities/subjects/sh2022004658 http://id.loc.gov/authorities/subjects/sh2022004540 |
title | Challenges for Arabic Machine Translation / |
title_auth | Challenges for Arabic Machine Translation / |
title_exact_search | Challenges for Arabic Machine Translation / |
title_full | Challenges for Arabic Machine Translation / Abdelhadi Soudi. |
title_fullStr | Challenges for Arabic Machine Translation / Abdelhadi Soudi. |
title_full_unstemmed | Challenges for Arabic Machine Translation / Abdelhadi Soudi. |
title_short | Challenges for Arabic Machine Translation / |
title_sort | challenges for arabic machine translation |
topic | Machine translating. English language Translating into Arabic. http://id.loc.gov/authorities/subjects/sh2022004658 Arabic language Translating into English. http://id.loc.gov/authorities/subjects/sh2022004540 Speech processing systems. Traduction automatique. Traitement automatique de la parole. Anglais (Langue) Traduction en arabe. Arabe (Langue) Traduction en anglais. FOREIGN LANGUAGE STUDY Arabic. bisacsh Arabic language Translating into English fast English language Translating into Arabic fast Machine translating fast Speech processing systems fast |
topic_facet | Machine translating. English language Translating into Arabic. Arabic language Translating into English. Speech processing systems. Traduction automatique. Traitement automatique de la parole. Anglais (Langue) Traduction en arabe. Arabe (Langue) Traduction en anglais. FOREIGN LANGUAGE STUDY Arabic. Arabic language Translating into English English language Translating into Arabic Machine translating Speech processing systems Electronic book. |
url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=471083 |
work_keys_str_mv | AT soudiabdelhadi challengesforarabicmachinetranslation AT farghalyali challengesforarabicmachinetranslation AT neumanngunter challengesforarabicmachinetranslation AT zbibrabih challengesforarabicmachinetranslation |