Results 31 to 40 of about 337,953 (200)
THE COMPARATIVE ANALYSIS OF THE MACHINE TRANSLATION SYSTEMS OF ECONOMIC DISCOURSE (ON THE EXAMPLE OF FRENCH-UKRAINIAN LANGUAGE PAIRS) [PDF]
Vìsnik Dnìpropetrovsʹkogo Unìversitetu Ekonomìki ta Prava Imenì Alʹfreda Nobelâ: Serìâ Fìlologìčnì Nauki, 2019 The paper is devoted to the research of the comparative analysis of the machine translation systems of French-language economic discourse in Ukrainian, taking into account the growing tendencies in the foreign economic activity of domestic enterprises ...
Nataliia M. Sopyluk, Ilona O. Tsarenko
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Comparison of SYSTRAN and Google Translate for English→Portuguese
Revista Tradumàtica, 2011 Two machine translation (MT) systems, a statistical MT (SMT) system and a hybrid system (rule-based and SMT) were tested in order to compare various MT performances. The source language was English (EN) and the target language Portuguese (PT).
Rodrigo Gomes de Oliveira +1 more
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DIGITALISED DELIVERY OF LANGUAGE. AN APPROACH TOWARDS MACHINE TRANSLATION TECHNOLOGY [PDF]
Carpathian Journal of Electrical Engineering, 2021 Unquestionably, in today’s language professionals, the use of information and communication technology (ICT) is already taken for granted and electronic handling as well as digitalized delivery of language services are standard client facilities.
Ioan Beniamin POP
doaj
A Survey of Orthographic Information in Machine Translation [PDF]
SN Computer Science (2021) 2:330, 2020 Machine translation is one of the applications of natural language processing which has been explored in different languages. Recently researchers started paying attention towards machine translation for resource-poor languages and closely related languages.
arxiv +1 more source
Self-aware cycle curriculum learning for multiple-choice reading comprehension [PDF]
PeerJ Computer Science, 2022 Multiple-choice reading comprehension task has recently attracted significant interest. The task provides several options for each question and requires the machine to select one of them as the correct answer.
Haihong Chen, Yufei Li
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Progress in Machine Translation
Engineering, 2022 After more than 70 years of evolution, great achievements have been made in machine translation. Especially in recent years, translation quality has been greatly improved with the emergence of neural machine translation (NMT).
Haifeng Wang +4 more
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Rule-Based Pronominal Anaphora Treatment for Machine Translation [PDF]
Proceedings of the Second Workshop on Discourse in Machine Translation, 2015 In this paper we describe the rule-based MT system Its-2 developed at the University of Geneva and submitted for the shared task on pronoun translation organized within the Second DiscoMT Workshop. For improving pronoun translation, an Anaphora Resolution (AR) step based on Chomsky’s Binding Theory and Hobbs’ algorithm has been implemented.
Sharid Loáiciga, Eric Wehrli
openaire +2 more sources
MACHINE TRANSLATION WITH JAVANESE SPEECH LEVELS’ CLASSIFICATION
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2016 A hybrid corpus-based machine processing has been developed to produce a proper Javanese speech level translation. The developed statistical memory-based machine translation shows significantly accurate results.
Andrew Nafalski, Aji Prasetya Wibawa
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USING MACHINE TRANSLATION ENGINES IN THE CLASSROOM: A SURVEY OF TRANSLATION STUDENTS’ PERFORMANCE
Novìtnâ Osvìta, 2020 This paper outlines the results of the experimental study aiming to explore the impact of using machine translation engines on the performance of translation students. Machine translation engines refer to the software developed to translate source texts
Alla Olkhovska, Iryna Frolova
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Automatic Classification of Human Translation and Machine Translation: A Study from the Perspective of Lexical Diversity [PDF]
arXiv, 2021 By using a trigram model and fine-tuning a pretrained BERT model for sequence classification, we show that machine translation and human translation can be classified with an accuracy above chance level, which suggests that machine translation and human translation are different in a systematic way. The classification accuracy of machine translation is
arxiv