1,052 research outputs found

    Extracting Directional and Comparable Corpora from a Multilingual Corpus for Translation Studies

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    Translation studies rely more and more on corpus data to examine specificities of translated texts, that can be translated from different original languages and compared to original texts. In parallel, more and more multilingual corpora are becoming available for various natural language processing tasks. This paper questions the use of these multilingual corpora in translation studies and shows the methodological steps needed in order to obtain more reliably comparable sub-corpora that consist of original and directly translated text only. Various experiments are presented that show the advantage of directional sub-corpora

    A Survey of Paraphrasing and Textual Entailment Methods

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    Paraphrasing methods recognize, generate, or extract phrases, sentences, or longer natural language expressions that convey almost the same information. Textual entailment methods, on the other hand, recognize, generate, or extract pairs of natural language expressions, such that a human who reads (and trusts) the first element of a pair would most likely infer that the other element is also true. Paraphrasing can be seen as bidirectional textual entailment and methods from the two areas are often similar. Both kinds of methods are useful, at least in principle, in a wide range of natural language processing applications, including question answering, summarization, text generation, and machine translation. We summarize key ideas from the two areas by considering in turn recognition, generation, and extraction methods, also pointing to prominent articles and resources.Comment: Technical Report, Natural Language Processing Group, Department of Informatics, Athens University of Economics and Business, Greece, 201

    Word-formation in original and translated English: source language influence on the use of un- and less

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    This article aims to assess whether the word-formation features of translated language, as opposed to original language, are source language (SL)-dependent or translation-related. To do so, we analyze the use of the -less and un- negative affixes in original English and in English translated from four SL: French, Italian, Dutch and German. Findings based on the Europarl corpus show that the use of -less and un- in translated English is partially SL-dependent

    The Effect of Normalization for Bi-directional Amharic-English Neural Machine Translation

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    Machine translation (MT) is one of the main tasks in natural language processing whose objective is to translate texts automatically from one natural language to another. Nowadays, using deep neural networks for MT tasks has received great attention. These networks require lots of data to learn abstract representations of the input and store it in continuous vectors. This paper presents the first relatively large-scale Amharic-English parallel sentence dataset. Using these compiled data, we build bi-directional Amharic-English translation models by fine-tuning the existing Facebook M2M100 pre-trained model achieving a BLEU score of 37.79 in Amharic-English 32.74 in English-Amharic translation. Additionally, we explore the effects of Amharic homophone normalization on the machine translation task. The results show that the normalization of Amharic homophone characters increases the performance of Amharic-English machine translation in both directions

    Exploring the use of parallel corpora in the complilation of specialised bilingual dictionaries of technical terms: a case study of English and isiXhosa

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    Text in EnglishAbstracts in English, isiXhosa and AfrikaansThe Constitution of the Republic of South Africa, Act 108 of 1996, mandates the state to take practical and positive measures to elevate the status and the use of indigenous languages. The implementation of this pronouncement resulted in a growing demand for specialised translations in fields like technology, science, commerce, law and finance. The lack of terminology and resources such as specialised bilingual dictionaries in indigenous languages, particularly isiXhosa remains a growing concern that hinders the translation and the intellectualisation of isiXhosa. A growing number of African scholars affirm the importance of specialised dictionaries in the African languages as tools for language and terminology development so that African languages can be used in the areas of science and technology. In the light of the background above, this study explored how parallel corpora can be interrogated using a bilingual concordancer, ParaConc to extract bilingual terminology that can be used to create specialised bilingual dictionaries. A corpus-based approach was selected due to its speed, efficiency and accuracy in extracting bilingual terms in their immediate contexts. In enhancing the research outcomes, Descriptive Translations Studies (DTS) and Corpus-based translation studies (CTS) were used in a complementary manner. Because the study is interdisciplinary, the function theories of lexicography that emphasise the function and needs of users were also applied. The analysis and extraction of bilingual terminology for dictionary making was successful through the use of the following ParaConc features, namely frequencies, hot word lists, hot words, search facility and concordances (Key Word in Context), among others. The findings revealed that English-isiXhosa Parallel Corpus is a repository of translation equivalents and other information categories that can make specialised dictionaries more user-friendly and multifunctional. The frequency lists were revealed as an effective method of selecting headwords for inclusion in a dictionary. The results also unraveled the complex functions of bilingual concordances where information on collocations and multiword units, sense distinction and usage examples could be easily identifiable proving that this approach is more efficient than the traditional method. The study contributes to the knowledge on corpus-based lexicography, standardisation of finance terminology resource development and making of user-friendly dictionaries that are tailor-made for different needs of users.Umgaqo-siseko weli loMzantsi Afrika ukhululele uRhulumente ukuba athabathe amanyathelo abonakalayo ekuphuhliseni nasekuphuculeni iilwimi zesiNtu. Esi sindululo sibangele ukwanda kokuguqulelwa kwamaxwebhu angezobuchwepheshe, inzululwazi, umthetho, ezemali noqoqosho angesiNgesi eguqulelwa kwiilwimi ebezifudula zingasiwe-so ezinjengesiXhosa. Ukunqongophala kwesigama kunye nezichazi-magama kube yingxaki enkulu ekuguquleleni ngakumbi izichazi-magama ezilwimi-mbini eziqulethe isigama esikhethekileyo. Iingcali ezininzi ziyangqinelana ukuba olu hlobo lwezi zichazi-magama luyimfuneko kuba ludlala iindima enkulu ekuphuhlisweni kweelwimi zesiNtu, ekuyileni isigama, nasekusetyenzisweni kwazo kumabakala obunzululwazi nobuchwepheshe. Olu phando ke luvavanya ukusetyenziswa kwekhophasi equlethe amaxwebhu esiNgesi neenguqulelo zawo zesiXhosa njengovimba wokudimbaza isigama sezemali esinokunceda ekuqulunqweni kwesichazi-magama esilwimi-mbini. Isizathu esibangele ukukhetha le ndlela yophando esebenzisa ikhompyutha kukuba iyakhawuleza, ulwazi oluthathwe kwikhophasi luchanekile, yaye isigama kwikhophasi singqamana ngqo nomxholo wamaxwebhu nto leyo eyenza kube lula ukufumana iintsingiselo nemizekelo ephilayo. Ukutyebisa olu phando indlela yekhophasi iye yaxhaswa zezinye iindlela zophando ezityunjiweyo: ufundo lwenguguqulelo oluchazayo (DTS) kunye neendlela zokuguqulela ezijoliswe kumsebenzi nakuhlobo lwabasebenzisi zinguqulelo ezo. Kanti ke ziqwalaselwe neenkqubo zophando lobhalo-zichazi-magama eziinjongo zokuqulunqa izichazi-magama ezesebenzisekayo neziluncedo kuninzi lwabasebenzisi zichazi-magama ngakumbi kwisizwe esisebenzisa iilwimi ezininzi. Ukuhlalutya nokudimbaza isigama kwikhophasi kolu phando kusetyenziswe isixhobo sekhompyutha esilungiselelwe ikhophasi enelwiimi ezimbini nangaphezulu ebizwa ngokuba yiParaConc. Iziphumo zolu phando zibonise mhlophe ukuba ikhophasi eneenguqulelo nguvimba weendidi ngendidi zamagama nolwazi olunokuphucula izichazi-magama zeli xesha. Kaloku abaguquleli basebenzise amaqhinga ngamaqhinga ukunika iinguqulelo bekhokelwa yimigomo nemithetho yoguqulelo enxuse abasebenzisi bamaxwebhu aguqulelweyo. Ubuchule beParaConc bokukwazi ukuhlela amagama ngokwendlela afumaneka ngayo kunye neenkcukacha zamanani budandalazise indlela eyiyo yokukhetha imichazwa enokungena kwisichazi-magama. Iziphumo zikwabonakalise iintlaninge yolwazi olufumaneka kwiKWIC, lwazi olo olungelula ukulufumana xa usebenzisa undlela-ndala wokwakha isichazi-magama. Esi sifundo esihlanganyele uGuqulelo olusekelwe kwiKhophasi noQulunqo-zichazi-magama zobuchwepheshe luya kuba negalelo elingathethekiyo kwindlela yokwakha izichazi-magama kwilwiimi zeSintu ngokubanzi nancakasana kwisiXhosa, nto leyo eya kothula umthwalo kubaqulunqi-zichazi-magama. Ukwakha nokuqulunqa izichazi-magama ezilwimi-mbini zezemali kuya kwandisa imithombo yesigama esinqongopheleyo kananjalo sivelise izichazi-magama eziluncedo kwisininzi sabantu.Die Grondwet van die Republiek van Suid-Afrika, Wet 108 van 1996, gee aan die staat die mandaat om praktiese en positiewe maatreรซls te tref om die status en gebruik van inheemse tale te verhoog. Die implementering van hierdie uitspraak het gelei tot โ€™n toenemende vraag na gespesialiseerde vertalings in domeine soos tegnologie, wetenskap, handel, regte en finansies. Die gebrek aan terminologie en hulpbronne soos gespesialiseerde woordeboeke in inheemse tale, veral Xhosa, wek toenemende kommer wat die vertaling en die intellektualisering van Xhosa belemmer. โ€™n Toenemende aantal vakkundiges in Afrika beklemtoon die belangrikheid van gespesialiseerde woordeboeke in die Afrikatale as instrumente vir taal- en terminologie-ontwikkeling sodat Afrikatale gebruik kan word in die areas van wetenskap en tegnologie. In die lig van die voorafgaande agtergrond het hierdie studie ondersoek ingestel na hoe parallelle korpora deursoek kan word deur โ€™n tweetalige konkordanser (ParaConc) te gebruik om tweetalige terminologie te ontgin wat gebruik kan word in die onwikkeling van tweetalige gespesialiseerde woordeboeke. โ€™n Korpusgebaseerde benadering is gekies vir die spoed, doeltreffendheid en akkuraatheid waarmee dit tweetalige terme uit hulle onmiddellike kontekste kan onttrek. Beskrywende Vertaalstudies (DTS) en Korpusgebaseerde Vertaalstudies (CTS) is op โ€™n aanvullende wyse gebruik om die navorsingsuitkomste te verbeter. Aangesien die studie interdissiplinรชr is, is die funksieteorieรซ van leksikografie wat die funksie en behoeftes van gebruikers beklemtoon, ook toegepas. Die analise en ontginning van tweetalige terminologie om woordeboeke te ontwikkel was suksesvol deur, onder andere, gebruik te maak van die volgende ParaConc-eienskappe, naamlik, frekwensies, hotword-lyste, hot words, die soekfunksie en konkordansies (Sleutelwoord-in-Konteks). Die bevindings toon dat โ€™n Engels-Xhosa Parallelle Korpus โ€™n bron van vertaalekwivalente en ander inligtingskategorieรซ is wat gespesialiseerde woordeboeke meer gebruikersvriendelik en multifunksioneel kan maak. Die frekwensielyste is geรฏdentifiseer as โ€™n doeltreffende metode om hoofwoorde te selekteer wat opgeneem kan word in โ€™n woordeboek. Die bevindings het ook die komplekse funksies van tweetalige konkordansers ontknoop waar inligting oor kollokasies en veelvuldigewoord-eenhede, betekenisonderskeiding en gebruiksvoorbeelde maklik identifiseer kon word wat aandui dat hierdie metode viii doeltreffender is as die tradisionele metode. Die studie dra by tot die kennisveld van korpusgebaseerde leksikografie, standaardisering van finansiรซle terminologie, hulpbronontwikkeling en die ontwikkeling van gebruikersvriendelike woordeboeke wat doelgemaak is vir verskillende behoeftes van gebruikers.Linguistics and Modern LanguagesD. Litt. et Phil. (Linguistics (Translation Studies)

    Bilingual Lexicon Extraction Using a Modified Perceptron Algorithm

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    ์ „์‚ฐ ์–ธ์–ดํ•™ ๋ถ„์•ผ์—์„œ ๋ณ‘๋ ฌ ๋ง๋ญ‰์น˜์™€ ์ด์ค‘์–ธ์–ด ์–ดํœ˜๋Š” ๊ธฐ๊ณ„๋ฒˆ์—ญ๊ณผ ๊ต์ฐจ ์ •๋ณด ํƒ์ƒ‰ ๋“ฑ์˜ ๋ถ„์•ผ์—์„œ ์ค‘์š”ํ•œ ์ž์›์œผ๋กœ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ๋ณ‘๋ ฌ ๋ง๋ญ‰์น˜๋Š” ๊ธฐ๊ณ„๋ฒˆ์—ญ ์‹œ์Šคํ…œ์—์„œ ๋ฒˆ์—ญ ํ™•๋ฅ ๋“ค์„ ์ถ”์ถœํ•˜๋Š”๋ฐ ์‚ฌ์šฉ๋œ๋‹ค. ์ด์ค‘์–ธ์–ด ์–ดํœ˜๋Š” ๊ต์ฐจ ์ •๋ณด ํƒ์ƒ‰์—์„œ ์ง์ ‘์ ์œผ๋กœ ๋‹จ์–ด ๋Œ€ ๋‹จ์–ด ๋ฒˆ์—ญ์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•œ๋‹ค. ๋˜ํ•œ ๊ธฐ๊ณ„๋ฒˆ์—ญ ์‹œ์Šคํ…œ์—์„œ ๋ฒˆ์—ญ ํ”„๋กœ์„ธ์Šค๋ฅผ ๋„์™€์ฃผ๋Š” ์—ญํ• ์„ ํ•˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ํ•™์Šต์„ ์œ„ํ•œ ๋ณ‘๋ ฌ ๋ง๋ญ‰์น˜์™€ ์ด์ค‘์–ธ์–ด ์–ดํœ˜์˜ ์šฉ๋Ÿ‰์ด ํฌ๋ฉด ํด์ˆ˜๋ก ๊ธฐ๊ณ„๋ฒˆ์—ญ ์‹œ์Šคํ…œ์˜ ์„ฑ๋Šฅ์ด ํ–ฅ์ƒ๋œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ์ด์ค‘์–ธ์–ด ์–ดํœ˜๋ฅผ ์ˆ˜๋™์œผ๋กœ, ์ฆ‰ ์‚ฌ๋žŒ์˜ ํž˜์œผ๋กœ ๊ตฌ์ถ•ํ•˜๋Š” ๊ฒƒ์€ ๋งŽ์€ ๋น„์šฉ๊ณผ ์‹œ๊ฐ„๊ณผ ๋…ธ๋™์„ ํ•„์š”๋กœ ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์ด์œ ๋“ค ๋•Œ๋ฌธ์— ์ด์ค‘์–ธ์–ด ์–ดํœ˜๋ฅผ ์ถ”์ถœํ•˜๋Š” ์—ฐ๊ตฌ๊ฐ€ ๋งŽ์€ ์—ฐ๊ตฌ์ž๋“ค์—๊ฒŒ ๊ฐ๊ด‘๋ฐ›๊ฒŒ ๋˜์—ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ด์ค‘์–ธ์–ด ์–ดํœ˜๋ฅผ ์ถ”์ถœํ•˜๋Š” ์ƒˆ๋กญ๊ณ  ํšจ๊ณผ์ ์ธ ๋ฐฉ๋ฒ•๋ก ์„ ์ œ์•ˆํ•œ๋‹ค. ์ด์ค‘์–ธ์–ด ์–ดํœ˜ ์ถ”์ถœ์—์„œ ๊ฐ€์žฅ ๋งŽ์ด ๋‹ค๋ฃจ์–ด์ง€๋Š” ๋ฒกํ„ฐ ๊ณต๊ฐ„ ๋ชจ๋ธ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜๊ณ , ์‹ ๊ฒฝ๋ง์˜ ํ•œ ์ข…๋ฅ˜์ธ ํผ์…‰ํŠธ๋ก  ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์‚ฌ์šฉํ•˜์—ฌ ์ด์ค‘์–ธ์–ด ์–ดํœ˜์˜ ๊ฐ€์ค‘์น˜๋ฅผ ๋ฐ˜๋ณตํ•ด์„œ ํ•™์Šตํ•œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๋ฐ˜๋ณต์ ์œผ๋กœ ํ•™์Šต๋œ ์ด์ค‘์–ธ์–ด ์–ดํœ˜์˜ ๊ฐ€์ค‘์น˜์™€ ํผ์…‰ํŠธ๋ก ์„ ์‚ฌ์šฉํ•˜์—ฌ ์ตœ์ข… ์ด์ค‘์–ธ์–ด ์–ดํœ˜๋“ค์„ ์ถ”์ถœํ•œ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ํ•™์Šต๋˜์ง€ ์•Š์€ ์ดˆ๊ธฐ์˜ ๊ฒฐ๊ณผ์— ๋น„ํ•ด์„œ ๋ฐ˜๋ณต ํ•™์Šต๋œ ๊ฒฐ๊ณผ๊ฐ€ ํ‰๊ท  3.5%์˜ ์ •ํ™•๋„ ํ–ฅ์ƒ์„ ์–ป์„ ์ˆ˜ ์žˆ์—ˆ๋‹ค1. Introduction 2. Literature Review 2.1 Linguistic resources: The text corpora 2.2 A vector space model 2.3 Neural networks: The single layer Perceptron 2.4 Evaluation metrics 3. System Architecture of Bilingual Lexicon Extraction System 3.1 Required linguistic resources 3.2 System architecture 4. Building a Seed Dictionary 4.1 Methodology: Context Based Approach (CBA) 4.2 Experiments and results 4.2.1 Experimental setups 4.2.2 Experimental results 4.3 Discussions 5. Extracting Bilingual Lexicons 4.1 Methodology: Iterative Approach (IA) 4.2 Experiments and results 4.2.1 Experimental setups 4.2.2 Experimental results 4.3 Discussions 6. Conclusions and Future Work

    Lost in parallel concordances

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