• International journal of advanced smart convergence
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• v.10 no.4
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• pp.165-171
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• 2021

The current study investigated cyber learners' use and perceptions of online machine translation (MT) tools. The results show that learners use several MT tools frequently and extensively for various second language learning (L2) purposes according to their needs. The learners' overall perceptions of using MT for English learning were generally positive. The learners reported several advantages of machine translation: ease of use, helpful feedback, effective revision, and facilitation of self-directed learning. At the same time, a considerable number of learners were aware of MT's drawbacks, such as awkward sentences, inaccurate grammar, and inappropriate words, and thus held a negative or skeptical view on the quality and accuracy of MT. These findings have important pedagogical implications for using MT in the context of a cyber university. For successful integration of MT in English classes, teachers need to provide appropriate guidelines and training that will help learners use MT effectively.

• ETRI Journal
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• v.37 no.3
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• pp.541-550
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• 2015

In this paper, we propose a classification-based approach for hybridizing statistical machine translation and rulebased machine translation. Both the training dataset used in the learning of our proposed classifier and our feature extraction method affect the hybridization quality. To create one such training dataset, a previous approach used auto-evaluation metrics to determine from a set of component machine translation (MT) systems which gave the more accurate translation (by a comparative method). Once this had been determined, the most accurate translation was then labelled in such a way so as to indicate the MT system from which it came. In this previous approach, when the metric evaluation scores were low, there existed a high level of uncertainty as to which of the component MT systems was actually producing the better translation. To relax such uncertainty or error in classification, we propose an alternative approach to such labeling; that is, a cut-off method. In our experiments, using the aforementioned cut-off method in our proposed classifier, we managed to achieve a translation accuracy of 81.5% - a 5.0% improvement over existing methods.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.105-114
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• 2007

This paper addresses a method for customizing an English-to-Korean machine translation system from general domain to patent domain. The customizing method consists of following steps: 1) linguistically studying about characteristics of patent documents, 2) extracting unknown words from large patent documents and constructing large bilingual terminology, 3) extracting and constructing the patent-specific translation patterns 4) customizing the translation engine modules of the existing general MT system according to linguistic study about characteristics of patent documents, and 5) evaluating the accuracy of translation modules and the translation quality. This research was performed under the auspices of the MIC (Ministry of Information and Communication) of Korean government during 2005-2006. The translation accuracy of the customized English-Korean patent translation system is 82.43% on the average in 5 patent fields (machinery, electronics, chemistry, medicine and computer) according to the evaluation of 7 professional human translators. In 2006, the patent MT system started an on-line patent MT service in IPAC (International Patent Assistance Center) under MOCIE (Ministry of Commerce, Industry and Energy) in Korea. In 2007, KIPO (Korean Intellectual Property Office) tries to launch an English-Korean patent MT service.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.165-171
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• 2018

As the artificial intelligence (AI) plays a crucial role in machine translation (MT) which has loomed large as a new translation paradigm, concerns have also arisen if MT can produce a quality product as human translation (HT) can. In fact, several MT experimental studies report cases in which the MT product called post-editing (PE) as equally as HT or often superior ([1],[2],[6]). As motivated from those studies on translation quality between HT and PE, this study set up an experimental situation in which Korean literature was translated into English, comparatively, by 3 translators and 3 post-editors. Afterwards, a group of 3 other Koreans checked for accuracy of HT and PE; a group of 3 English native speakers scored for fluency of HT and PE. The findings are (1) HT took the translation time, at least, twice longer than PE. (2) Both HT and PE produced similar error types, and Mistranslation and Omission were the major errors for accuracy and Grammar for fluency. (3) HT turned to be inferior to PE for both accuracy and fluency.

• Korean Journal of Cognitive Science
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• v.12 no.4
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• pp.11-27
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• 2001

Machine translation (MT) quality assessment is an outstanding problem. In the present situation in which the quality of machine-translated products are far from the user\\`s satisfaction objective evaluation of MT system is a prerequisite to building mutual trust between the users and the vendors stimulating constructive competition among the developers and finally leading to improve the quality of MT systems. Especially there emerges a need for an intensive study on how to evaluate the quality of MT systems from both linguistic and data processing aspects and to secure a steady improvement of the translation quality. With due regard to such points we in this paper present a linguistic evaluation of English-to-Korean machine translation based on a test suite composed of 3.373 sentences that were classified into their linguistic phenomena and complexity levels and report the experimental results made from several commercial MT systems.

• Language and Information
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• v.3 no.1
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• pp.65-82
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• 1999

The interests in Machine Translation(MT) have gotten revitalized lately with the rapid expansion of internet users. MT technology has gone through several different stages of development, but the longest surviving methods usually maintains the following characteristics: the expand ability and flexibility based on proved linguistic formalism, the transfer method of translation, the continued efforts of systematic updates being made into the system. This paper introduces one such system, L&H Korean-English bidirectional MT system. This system uses Lexical-Functional Grammar as its linguistic framework. It also adopts the transfer method of MT and has been around on the market for over 10 years for other language pairs. Currently, the system covers over 10 different languages including Chinese, Japanese and Arabic, in addition to European languages. This paper will review the system in its core and discuss related tools and resources be ing used to enhance the quality of translation.

• Genomics & Informatics
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• v.18 no.2
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• pp.21.1-21.7
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• 2020

Scientific research is mostly published in English, regardless of the researcher's nationality. However, this growing practice impairs or hinders the comprehension of professionals who depend on the results of these studies to provide adequate care for their patients. We suggest that machine translation (MT) can be used as a way of providing useful translation for biomedical articles, even though the translation itself may not be fluent. To tackle possible mistranslation that can harm a patient, we resort to crowd-sourced validation of translations. We developed a prototype of MT validation and edition, where users can vote for that translation as valid, or suggest modifications (i.e., post-editing the MT). A glossary match system is also included, aiming at terminology consistency.

• Language and Information
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• v.2 no.1
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• pp.1-41
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• 1998

Evaluation of multilingual translation fundamentally involves measurement of meaning equivalences between the formally mapped discourses/texts of SL(source language) and TL(target language) both represented by a metalanguage called IL(interlingua). Unlike a usaal uni-directional MT(machine translation) model(e.g.:SL $\rightarrow$ analysis $\rightarrow$ transfer $\rightarrow$ generation $\rightarrow$ TL), a bi-directional(by 'negotiation') model(i.e.: SL $\rightarrow$ IL/S $\leftrightarrow$ IL $\leftrightarrow$ IL/T \leftarrow TL) is proposed here for the purpose of evaluating multilingual, not merely bilingual, translation. The IL, as conceived of in this study, is an English-based predicate logic represented in the framework of MRS(minimal recursion semantics), an MT-oriented off-shoot of HPSG(Head-driven Phrase Structure Grammar). In addition, a list of semantic and pragmatic checkpoints are set up, some being optional depending on the kind and use of the translation, so sa to have the evaluation of translation fine-grained by computing matching or mismatching of such checkpoints.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06c
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• pp.351-357
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• 1994

At least two projects for English-to-Korean translation have been already in action for the last few years, but so far no attention has been paid to the problem of resolving pronominal reference and a default pronoun translation has been considered instead. In this paper we argue that pronous cannot be handled trivially in an English-to-Korean translation and one cannot bypass the task of resolving anaphoric reference if aiming at good and natural translation. In addition, we propose lexical transfer rules for English-to-Korean anaphor translation and outline an anaphora resolution model for an English-to-Korean MT system in operation.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.144-150
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• 2023

With progressive advancements in Man-made consciousness (computer based intelligence) and Profound Learning (DL), contributing altogether to Normal Language Handling (NLP), the precision and nature of Machine Interpretation (MT) has worked on complex. There is a discussion, but that its no time like the present the human interpretation became immaterial or excess. All things considered, human flaws are consistently dealt with by its own creations. With the utilization of brain networks in machine interpretation, its been as of late guaranteed that keen frameworks can now decipher at standard with human interpreters. In any case, simulated intelligence is as yet not without any trace of issues related with handling of a language, let be the intricacies and complexities common of interpretation. Then, at that point, comes the innate predispositions while planning smart frameworks. How we plan these frameworks relies upon what our identity is, subsequently setting in a one-sided perspective and social encounters. Given the variety of language designs and societies they address, their taking care of by keen machines, even with profound learning abilities, with human proficiency looks exceptionally far-fetched, at any rate, for the time being.