{"?xml":{"@version":"1.0"},"edm:RDF":{"@xmlns:dc":"http://purl.org/dc/elements/1.1/","@xmlns:edm":"http://www.europeana.eu/schemas/edm/","@xmlns:wgs84_pos":"http://www.w3.org/2003/01/geo/wgs84_pos","@xmlns:foaf":"http://xmlns.com/foaf/0.1/","@xmlns:rdaGr2":"http://rdvocab.info/ElementsGr2","@xmlns:oai":"http://www.openarchives.org/OAI/2.0/","@xmlns:owl":"http://www.w3.org/2002/07/owl#","@xmlns:rdf":"http://www.w3.org/1999/02/22-rdf-syntax-ns#","@xmlns:ore":"http://www.openarchives.org/ore/terms/","@xmlns:skos":"http://www.w3.org/2004/02/skos/core#","@xmlns:dcterms":"http://purl.org/dc/terms/","edm:WebResource":[{"@rdf:about":"http://www.dlib.si/stream/URN:NBN:SI:doc-X6RS1N26/c4b984e4-161d-42c3-bcb9-3dc5277eaf29/PDF","dcterms:extent":"434 KB"},{"@rdf:about":"http://www.dlib.si/stream/URN:NBN:SI:doc-X6RS1N26/33601469-ca30-437b-8751-3823b1ef7dbc/TEXT","dcterms:extent":"69 KB"}],"edm:TimeSpan":{"@rdf:about":"2009-2025","edm:begin":{"@xml:lang":"en","#text":"2009"},"edm:end":{"@xml:lang":"en","#text":"2025"}},"edm:ProvidedCHO":{"@rdf:about":"URN:NBN:SI:doc-X6RS1N26","dcterms:isPartOf":[{"@rdf:resource":"https://www.dlib.si/details/URN:NBN:SI:spr-GMZ1HMBU"},{"@xml:lang":"sl","#text":"Vestnik za tuje jezike"}],"dcterms:issued":"2024","dc:creator":"Zinhom, Haithm","dc:format":[{"@xml:lang":"sl","#text":"številka:1"},{"@xml:lang":"sl","#text":"letnik:16"},{"@xml:lang":"sl","#text":"str. 175-198"}],"dc:identifier":["DOI:10.4312/vestnik.16.175-198","ISSN:1855-8453","COBISSID_HOST:227672323","URN:URN:NBN:SI:doc-X6RS1N26"],"dc:language":"en","dc:publisher":{"@xml:lang":"sl","#text":"Založba Univerze v Ljubljani"},"dc:subject":[{"@xml:lang":"en","#text":"applied approach"},{"@xml:lang":"en","#text":"Arabic"},{"@xml:lang":"en","#text":"artificial intelligence"},{"@xml:lang":"en","#text":"colloquial, slang"},{"@xml:lang":"en","#text":"English"},{"@xml:lang":"sl","#text":"ljudski jezik"},{"@xml:lang":"en","#text":"machine translation"},{"@xml:lang":"sl","#text":"pogovorni jezik"},{"@xml:lang":"sl","#text":"sleng"},{"@xml:lang":"sl","#text":"sodobna angleščina"},{"@xml:lang":"sl","#text":"sodobna standardna arabščina"},{"@xml:lang":"sl","#text":"strojno prevajanje"},{"@xml:lang":"sl","#text":"teorije prevajanja"},{"@xml:lang":"en","#text":"translation theorie"},{"@xml:lang":"sl","#text":"umetna inteligenca"},{"@xml:lang":"en","#text":"vernacular"}],"dcterms:temporal":{"@rdf:resource":"2009-2025"},"dc:title":{"@xml:lang":"sl","#text":"The challenges of using machine translation in rendering arabic texts into English| an applied perspective|"},"dc:description":[{"@xml:lang":"sl","#text":"Regardless of recent arguments about the wide-scale capabilities of artificial intelligence introduced into machine translation (MT) systems, some professionals still underestimate this new ap-proach, while others scholars see it as an opportunity to develop and improve the translation industry. There is no doubt that machine translation has massively impacted the translation profession and radically changed the way people interact through languages. Therefore, translators, university professors, and translation companies are all seeking to adapt to these radical transformations in the field of translation studies. Regardless of the advantages of MT, it still confronts huge challenges especially when applied to specific texts in different contexts, and particularly the colloquial Arabic that is very common in contemporary literature and mass media. On this basis and in response to repeated claims about the high efficiency of MT and its extraordinary potential to render any text from one language into another with accuracy and precision, this paper emphasizes the inability of MT systems to render Arabic texts into English, and vice versa. The paper emphasizes the damaging impact of using MT in rendering into English not only colloquial Arabic dialects but also modern standard Arabic (MSA). The paper also highlights the translation errors resulting from the use of MT in rendering modern English texts into Arabic and vice versa, with a focus on the translation of idiomatic expressions and proverbs. As an applied study, the paper uses a variety of texts selected from various literary and non-literary sources/contexts and translates them using Google Translate to show the drawbacks of MT, which caused a distortion of the meaning of the SL texts translated into TL. In other words, the paper aims to uncover the mistakes resulting from the use of MT when converting both MSA and colloquial Arabic expressions into English, and vice versa. The argument of the paper consists of four parts, including an introduction, which introduces contemporary translation theories, followed by a discussion of the challenges confronting Arabic-English translation, and examples of Arabic/English/Arabic translations carried out by machine and human translators, in addition to a conclusion"},{"@xml:lang":"sl","#text":"Ne glede na nedavne argumente o širokih zmožnostih umetne inteligence v sistemih strojnega prevajanja (MT) nekateri strokovnjaki še vedno podcenjujejo ta novi pristop, drugi pa v njem vidijo priložnost za razvoj in izboljšanje prevajalske industrije. Ni dvoma, da je strojno prevajanje močno vplivalo na prevajalsko stroko in korenito spremenilo način, kako ljudje komunicirajo prek jezikov. Zato se prevajalci, univerzitetni profesorji in prevajalska podjetja skušajo prilagoditi tem velikim spremembam na področju prevajalskih študij. Ne glede na prednosti MT se ta še vedno sooča z velikimi izzivi, zlasti pri uporabi za specifična besedila v različnih kontekstih, zlasti za pogovorno arabščino, ki je zelo pogosta v sodobni literaturi in množičnih medijih. Na podlagi tega in kot odgovor na ponavljajoče se trditve o visoki učinkovitosti MT in njegovem izjemnem potencialu, da natančno in natančno pretvori katerokoli besedilo iz enega jezika v drugega, ta čla-nek poudarja nezmožnost sistemov MT za pretvorbo arabskih besedil v angleščino in obratno. V prispevku je poudarjen škodljiv vpliv uporabe MT pri prevajanju v angleščino ne le pogovornih arabskih narečij, temveč tudi sodobne standardne arabščine (MSA). V prispevku so izpostavljene tudi napake pri prevajanju, ki so posledica uporabe MT pri prevajanju sodobnih angleških besedil v arabščino in obratno, s poudarkom na prevajanju idiomatskih izrazov in pregovorov. V članku kot primeru uporabne študije so uporabljena različna besedila, vzeta iz različnih literarnih in neli-terarnih virov/kontekstov, ki so prevedena s pomočjo Googlovega prevajalnika, da bi se pokazale pomanjkljivosti MT, ki so povzročile izkrivljanje pomena SL besedil, prevedenih v TL. Z drugimi besedami, namen prispevka je odkriti napake, ki so posledica uporabe MT pri pretvorbi tako MSA kot pogovornih arabskih izrazov v angleščino in obratno. Argumentacija prispevka je sestavljena iz štirih delov, med katerimi so uvod, v katerem so predstavljene sodobne teorije prevajanja, sledi razprava o izzivih, s katerimi se sooča arabsko-angleško prevajanje, in primeri arabsko-angleških/arabskih prevodov, ki so jih naredili strojni in človeški prevajalci, poleg tega pa sledi še sklep"}],"edm:type":"TEXT","dc:type":[{"@xml:lang":"sl","#text":"znanstveno časopisje"},{"@xml:lang":"en","#text":"journals"},{"@rdf:resource":"http://www.wikidata.org/entity/Q361785"}]},"ore:Aggregation":{"@rdf:about":"http://www.dlib.si/?URN=URN:NBN:SI:doc-X6RS1N26","edm:aggregatedCHO":{"@rdf:resource":"URN:NBN:SI:doc-X6RS1N26"},"edm:isShownBy":{"@rdf:resource":"http://www.dlib.si/stream/URN:NBN:SI:doc-X6RS1N26/c4b984e4-161d-42c3-bcb9-3dc5277eaf29/PDF"},"edm:rights":{"@rdf:resource":"http://creativecommons.org/licenses/by-sa/4.0/"},"edm:provider":"Slovenian National E-content Aggregator","edm:intermediateProvider":{"@xml:lang":"en","#text":"National and University Library of Slovenia"},"edm:dataProvider":{"@xml:lang":"sl","#text":"Univerza v Ljubljani, Filozofska fakulteta"},"edm:object":{"@rdf:resource":"http://www.dlib.si/streamdb/URN:NBN:SI:doc-X6RS1N26/maxi/edm"},"edm:isShownAt":{"@rdf:resource":"http://www.dlib.si/details/URN:NBN:SI:doc-X6RS1N26"}}}}