60:
27:
279:
elements represented in only one corpus in order to extract cleaner parallel fragments of bilingual elements. Comparable corpora are used to directly obtain knowledge for translation purposes. High-quality parallel data is difficult to obtain, however, especially for under-resourced languages.
338:
have some similarities with translation memories. The most salient difference is that a translation memory loses the original context, while a bitext retains the original sentence order. That said, some implementations of translation memory, such as
361:
In his original 1988 article, Harris also posited that bitext represents how translators hold their source and target texts together in their mental working memories as they progress. However, this hypothesis has not been followed up.
485:
Abdallah, A. (2021). Impact of using parallel text strategy on teaching reading to intermediate II level students. International
Journal on Social and Education Sciences (IJonSES), 3(1), 95-108.
313:, which automatically aligns the original and translated versions of the same text. The tool generally matches these two texts sentence by sentence. A collection of bitexts is called a
241:
contains bilingual sentences that are not perfectly aligned or have poor quality translations. Nevertheless, most of its contents are bilingual translations of a specific document.
268:
algorithms are usually extracted from large bodies of similar sources, such as databases of news articles written in the first and second languages describing similar events.
234:
contains translations of the same document in two or more languages, aligned at least at the sentence level. These tend to be rarer than less-comparable corpora.
921:
1081:
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research. During translation, sentences can be split, merged, deleted, inserted or reordered by the translator. This makes alignment a non-trivial task.
358:, not by a machine. As such, small alignment errors or minor discrepancies that would cause a translation memory to fail are of no importance.
1059:
365:
Online bitexts and translation memories may also be called online bilingual concordances. Several are available on the public Web, including
880:
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However, extracted fragments may be noisy, with extra elements inserted in each corpus. Extraction techniques can differentiate between
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558:
193:
47:
1639:
731:
810:
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500:"Noisy-Parallel and Comparable Corpora Filtering Methodology for the Extraction of Bi-Lingual Equivalent Data at Sentence Level"
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may contain the original languages and a translation, or several translations by themselves, for ease of comparison and study;
1675:
Proceedings of the 5th
International Conference on Language Resources and Evaluation (LREC'2006). Genoa, Italy, 24–26 May 2006
470:
443:
124:
1669:
Ralf, Ralf
Steinberger; Pouliquen, Bruno; Widiger, Anna; Ignat, Camelia; Erjavec, Tomaž; Tufiş, Dan; Varga, Dániel (2006).
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TERMSEARCH – English/Russian/French parallel corpora (Major international treaties, conventions, agreements, etc.
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is built from non-sentence-aligned and untranslated bilingual documents, but the documents are topic-aligned.
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includes very heterogeneous and non-parallel bilingual documents that may or may not be topic-aligned.
184:(Greek for "sixfold") placed six versions of the Old Testament side by side. A famous example is the
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and Their
Reliability Through a Contrastive Analysis of Complex Prepositions from French to English
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is the identification of the corresponding sentences in both halves of the parallel text. The
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is a merged document composed of both source- and target-language versions of a given text.
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207:). Alignments of parallel corpora at sentence level are prerequisite for many areas of
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WeBiText: Building Large
Heterogeneous Translation Memories from Parallel Web Content
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Language Grid – Multilingual service platform that includes parallel text services
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Désilets, Alain; Farley, Benoît; Stojanović, Marta; Patenaude, Geneviève (2008).
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651:. Proceedings of Translating and the Computer. Vol. 30. pp. 27–28.
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31:
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An implementation of the Gale and Church sentence alignment algorithm (2005)
612:(M.A. thesis). Université catholique de Louvain & Universitetet i Oslo.
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766:, concordancer (open source AGPL) with online search on JCR and UNO corpus
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The JRC-Acquis: A multilingual aligned parallel corpus with 20+ languages
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Proceedings of the 2005 Workshop on
Building and Using Parallel Texts
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Proceedings of the 2003 Workshop on
Building and Using Parallel Texts
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Parallel text processing bibliography by J. Veronis and M.-D. Mahimon
700:
The Opus project aims at collecting freely available parallel corpora
593:
How
Reliable Are Online Bilingual Concordancers? An investigation of
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Williams, Philip; Sennrich, Rico; Post, Matt; Koehn, Philipp (2016).
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Bleualign – machine translation based sentence alignment (2010)
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Japanese-English
Bilingual Corpus of Knowledge's Kyoto Articles
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Parallel corpora can be classified into four main categories:
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are two examples of dual-language series of texts. Reference
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is a text placed alongside its translation or translations.
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ParaSol – A parallel corpus of Slavic and other languages
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European
Parliament Proceedings Parallel Corpus 1996–2011
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multilingual parallel corpora, online search interface.
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Bitexts are generated by a piece of software called an
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TradooIT – English/French/Spanish – Free Online tools
16:
Text placed alongside its translation or translations
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Uplug – tools for processing parallel corpora (2003)
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Nunavut Hansard – English/Inuktitut parallel corpus
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347:format for exchanging translation memories between
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84:. Unsourced material may be challenged and removed.
1685:
1132:
435:Routledge Encyclopedia of Translation Technology
354:Bitexts are designed to be consulted by a human
929:
199:Large collections of parallel texts are called
559:"Bi-Text, A New Concept in Translation Theory"
915:
717:COMPARA – Portuguese/English parallel corpora
38:engraved with the same decree in both of the
895:Web Alignment Tool at University of Grenoble
890:Vecalign sentence alignment algorithm (2019)
462:Syntax-based Statistical Machine Translation
221:
679:The JRC-Acquis Multilingual Parallel Corpus
321:, and can be consulted with a search tool.
922:
908:
755:InterCorp: A multilingual parallel corpus
617:
533:
515:
275:elements represented in both corpora and
144:Learn how and when to remove this message
878:Hierarchical alignment tool (HAT) (2018)
264:Large corpora used as training sets for
25:
589:
425:
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742:Glosbe: Multilanguage parallel corpora
556:
903:
1381:Simple Knowledge Organization System
848:The Hunalign sentence aligner (2005)
497:
431:
82:adding citations to reliable sources
53:
672:
634:"TradooIT – Concordancier bilingue"
487:https://doi.org/10.46328/ijonses.48
259:
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826:
792:and other public documents of the
14:
1715:
1396:Thesaurus (information retrieval)
863:Gargantua sentence aligner (2010)
757:40 languages aligned with Czech,
667:
393:Example-based machine translation
804:
325:Bitexts and translation memories
58:
772:, with online search interface.
413:Statistical machine translation
69:needs additional citations for
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977:Natural language understanding
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214:Parallel texts may be used in
188:, whose discovery allowed the
50:the Ancient Egyptian language.
1:
1501:Optical character recognition
418:
349:computer-assisted translation
1194:Multi-document summarization
833:GIZA++ alignment tool (1999)
751:with online search interface
7:
1524:Latent Dirichlet allocation
1496:Natural language generation
1361:Machine-readable dictionary
1356:Linguistic Linked Open Data
931:Natural language processing
398:Natural language processing
388:Computer-assisted reviewing
376:
341:Translation Memory eXchange
46:. Its discovery was key to
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1276:Explicit semantic analysis
1025:Deep linguistic processing
535:10.7494/csci.2015.16.2.169
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1119:Word-sense disambiguation
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972:Computational linguistics
937:
557:Harris, B. (March 1988).
465:. Morgan & Claypool.
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222:Types of parallel corpora
190:Ancient Egyptian language
1645:Natural Language Toolkit
1569:Pronunciation assessment
1471:Automatic identification
1301:Latent semantic analysis
1257:Distributional semantics
1142:Compound-term processing
1040:Named-entity recognition
691:with 231 language pairs.
498:Wołk, Krzysztof (2015).
40:Ancient Egyptian scripts
19:Not to be confused with
1549:Automated essay scoring
1519:Document classification
1186:Automatic summarization
782:EUR-Lex Corpus – corpus
759:online search interface
590:Genette, Marie (2016).
253:quasi-comparable corpus
162:Parallel text alignment
1406:Universal Dependencies
1099:Terminology extraction
1082:Semantic decomposition
1077:Semantic role labeling
1067:Part-of-speech tagging
1035:Information extraction
1020:Coreference resolution
1010:Collocation extraction
572:: 8–10. Archived from
432:Chan, Sin-Wai (2015).
166:Loeb Classical Library
51:
1694:Translation databases
1167:Sentence segmentation
788:database consists of
681:of the total body of
438:. London: Routledge.
383:Bilingual inscription
290:Bitext word alignment
239:noisy parallel corpus
170:Clay Sanskrit Library
29:
1699:Language acquisition
1619:Voice user interface
1330:datasets and corpora
1271:Document-term matrix
1124:Word-sense induction
688:Acquis Communautaire
78:improve this article
1599:Interactive fiction
1529:Pachinko allocation
1486:Speech segmentation
1442:Google Ngram Viewer
1214:Machine translation
1204:Text simplification
1199:Sentence extraction
1087:Semantic similarity
858:mALIGNa (2008–2020)
526:2015arXiv151004500W
296:translation studies
266:machine translation
1704:Corpus linguistics
1609:Question answering
1481:Speech recognition
1346:Corpus linguistics
1326:Language resources
1109:Textual entailment
1092:Sentiment analysis
883:2020-07-05 at the
853:Champollion (2006)
790:European Union law
747:2013-05-27 at the
710:2012-08-22 at the
343:(TMX), a standard
331:Translation memory
216:language education
52:
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1614:Virtual assistant
1539:Computer-assisted
1465:
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1222:Computer-assisted
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1172:Word segmentation
1134:Text segmentation
1072:Semantic analysis
1060:Syntactic parsing
1045:Ontology learning
472:978-1-62705-502-4
445:978-1-315-74912-9
246:comparable corpus
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1635:Formal semantics
1584:Natural language
1491:Speech synthesis
1473:and data capture
1376:Semantic network
1351:Lexical resource
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1152:Lexical analysis
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1055:Semantic parsing
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373:, and Tradooit.
319:bilingual corpus
294:In the field of
260:Noise in corpora
201:parallel corpora
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1030:Distant reading
1005:Argument mining
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579:on 2018-03-02.
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873:YASA (2013)
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277:monolingual
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48:deciphering
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1114:Truecasing
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517:1510.04500
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356:translator
209:linguistic
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273:bilingual
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