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Al-Tuwayrish, Raneem Khalid – Advances in Language and Literary Studies, 2016
Artificial Intelligence or AI as it is popularly known and its corollary, Machine Translation (MT) have long engaged scientists, thinkers and linguists alike in the twenty first century. However, the wider question that lies in the relation between technology and translation is, What does technology do to language? This is an important question in…
Descriptors: Foreign Countries, Computational Linguistics, Translation, Second Language Learning
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Eyckmans, June; Lindstromberg, Seth – Language Teaching Research, 2017
Corpus analyses of learners' dictionaries of English idioms have revealed that 11% to 35% of English figurative idioms show either alliteration ("miss the mark") or assonance ("get this show on the road"), depending on the type considered. Because English multiword combinations, particularly idiomatic expressions, present a…
Descriptors: Second Language Learning, English (Second Language), Figurative Language, Phonology
O'Neill, Errol Marinus – ProQuest LLC, 2012
Online translation (OT) sites such as Free Translation and Babel Fish are freely available to the general public and purport to convert inputted text, from single words to entire paragraphs, instantly from one language to another. Discussion in the literature about OT for second-language (L2) acquisition has generally focused either on the…
Descriptors: French, Second Language Learning, Translation, Computational Linguistics
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Jafarpour, Ali Akbar; Sharifi, Abolghasem – Teaching English with Technology, 2012
Collocations are one of the most important elements in language proficiency but the effect of error correction feedback of collocations has not been thoroughly examined. Some researchers report the usefulness and importance of error correction (Hyland, 1990; Bartram & Walton, 1991; Ferris, 1999; Chandler, 2003), while others showed that error…
Descriptors: Error Correction, Feedback (Response), Phrase Structure, Language Proficiency