• Proceedings of the Korean Society for Cognitive Science Conference
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• 2005.05a
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• pp.255-260
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• 2005

번역 메모리(Translation Memory)는 오늘날 기계번역에 있어 통계기반 접근법이나 형태-통사적 접근법 모두에 있어 가장 중요한 요소로 평가되고 있다. 그러나 번역 메모리는 언어의 자질 및 각 용례를 통합적으로 관리해야 하며, 이를 기계가 자동으로 처리해주어야 하는 어려움이 있다. 최근에는 이러한 문제점을 해결하기 위해 다국적 기업을 중심으로 기계보조번역(Computer Aided Translation) 환경에 대한 연구가 활발히 이루어지고 있으나, 언어적인 특성 보다는 번역 메모리의 저장/대치적 측면에서 주요 연구가 이루어지고 있다. 이 논문에서는 번역 메모리 정보가 보다 높은 재사용성을 보이기 위해서는 다양한 언어자질값을 담을 수 있어야 한다고 보고, 이를 효율적으로 관리/구축할 수 있는 기계보조번역 워크벤치의 framework을 제시한다. 언어분석을 위한 대상언어로는 교역 및 기술 측면에서 영어, 일어, 중국어 다음으로 영향력이 높은 불어를 채택하며, 기존 기계보조번역 방식에 대한 고찰을 통해 개선된 번역 메모리 관리, 자동분석/번역 모듈 및 협업(collaboration) 방안에 대해 소개하고, 향후 발전방향에 대해 논의한다.

• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.15-20
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• 2019

As the machine learning research has developed, the field of translation and image analysis such as optical character recognition has made great progress. However, video translation that combines these two is slower than previous developments. In this paper, we develop an image translator that combines existing OCR technology and translation technology and verify its effectiveness. Before developing, we presented what functions are needed to implement this system and how to implement them, and then tested their performance. With the application program developed through this paper, users can access translation more conveniently, and also can contribute to ensuring the convenience provided in any environment.

• Annual Conference on Human and Language Technology
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• 2011.10a
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• pp.147-150
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• 2011

본 논문에서는 병렬 말뭉치에서 오류가 있을 것으로 추정되는 문장을 자동 추출하여, 다수의 번역 사전 구축 작업자가 자동 번역시스템을 직접 사용하면서 번역 사전을 튜닝하는 방법에 대하여 제안하고자 한다. 작업자는 병렬 말뭉치의 대역문을 이용하여 자동 번역 결과의 BLEU를 측정하고, 사전 수정 전과 후의 BLEU 차이를 정량적으로 제시해 줌으로써 양질의 번역 사전을 구축하도록 하였다. 대량의 번역 사전이 이미 구축된 자동 번역시스템에서 추가적인 성능향상을 위해 대량의 말뭉치에서 미등록어, 번역패턴 등을 추출하여, 대량으로 구축하는 기존 방법에 비해 사전 구축 부작용이 적으며, 자동번역 성능향상에 더 기여하는 것을 실험을 통해 증명하였다. 이를 위해 본 논문에서는 중한 자동 번역시스템을 대상으로, 중국어 문장 2,193문장에 대해, 사전 구축 작업자 2명이 2주간 튜닝한 결과와 15만 말뭉치에서 추출한 미등록어 후보 2만 엔트리를 3명의 사전 구축 작업자가 미등록어 선별, 품사 및 대역어 부착한 결과 7,200 엔트리를 대상으로 자동평가를 실시하였다. 실험결과 미등록어 추가에 의한 BLEU 성능향상은 +3인데 반해, 약 2,000문장 튜닝 후 BLEU를 +12 향상시켰다.

• Journal of Digital Contents Society
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• v.19 no.6
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• pp.1161-1167
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• 2018

The development of machine learning has enabled machines to perform delicate tasks that only humans could do, and thus many companies have introduced machine learning based translators. Existing translators have good performances but they have problems in number translation. The translators often mistranslate numbers when the input sentence includes a large number. Furthermore, the output sentence structure completely changes even if only one number in the input sentence changes. In this paper, first, we optimized a neural machine translation model architecture that uses bidirectional RNN, LSTM, and the attention mechanism through data cleansing and changing the dictionary size. Then, we implemented a number-processing algorithm specialized in number translation and applied it to the neural machine translation model to solve the problems above. The paper includes the data cleansing method, an optimal dictionary size and the number-processing algorithm, as well as experiment results for translation performance based on the BLEU score.

• Korean Journal of Cognitive Science
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• v.15 no.2
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• pp.33-42
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• 2004

There are many syntactic similarities between Japanese and Korean language. These similarities enable us to build Japanese-Korean translation systems without depending cm sophisticated syntactic analysis and semantic analysis. To further improve translation accuracy, we have been developing a Japanese-Korean translation system using these similarities for several years. However, there still remain some problems with regard to translation of inflected words, processing of multi-translatable words and so on. In this paper, we propose a new method for Japanese-Koran machine translation by using the relationships of two neighboring words. To solve the problems, we investigate the connection rules of auxiliary verb priority. And we design the translation table, which consists of entry tables and connection form tables. for unambiguous words, we can translate a Japanese word to the corresponding Korean word in terms of direct-matching method by consulting the only entry table. Otherwise we have to evaluate the connection value computed from connection form tables and then we can select the most appropriate target word.

• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.998-1008
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• 2004

There are many syntactic similarities between Japanese and Korean languages. Using these similarities, we can make out the Japanese-Korean translation system without most of syntactic analysis and semantic analysis. To improve the translation rates greatly, we have been developing the Japanese-Korean translation system using these similarities from several years ago. However, the system remains some problems such as a translation of inflected words, processing of multi-translatable words and so on. In this paper, we suggest the new method of Japanese-Korean translation by using relations of two neighboring words. To solve the problems, we investigated the connection rules of auxiliary verbs priority. And we design the translation table which is consists of entry tables and connection forms tables. A case of only one translation word, we can translate a Korean to Japanese by direct matching method use of only entry table, otherwise we have to evaluate the connection value by connection forms tables and then we can select the best translation word.

• The Transactions of the Korea Information Processing Society
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• v.5 no.3
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• pp.681-687
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• 1998

The paper presents a hybrid mcthod for disambiguation of the verb meaning in the machine translation. The presented verb translation algorithm is to perform the concept-based method and the statistics-based method simultaneously. It uses a collocation dictionary, WordNct and the statistical information extracted from corpus. In the transfer phase of the machine translation, it tries to find the target word of the source verb. If it fails, it refers to Word Net to try to find it by calculating word similarities between the logical constraints of the source sentence and those in the collocation dictionary. At the same time, it refers to the statistical information extracted from corpus to try to find it by calculating co-occurrence similarity knowledge. The experimental result shows that the algorithm performs more accurate verb translation than the other algorithms and improves accuracy of the verb translation by 24.8% compared to the collocation-based method.

• The Korean Publising Journal, Monthly
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• s.244
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• pp.9-9
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• 1998

고전 번역자의 부족, 영세출판사의 상업주의, 고전번역에 대한 정부의 무관심 등이 고전을 번역하지 않는 악순환을 거듭하게 한다.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.403-408
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• 2022

This study analyzed the translation strategies of four Chinese translations of 『Who ate all the Sing a?』. As is well known, Park Wan-seo's works contain many psychological descriptions, abstract vocabulary, idioms, proverbs, dialects, etc., so when translating into Chinese, various translation strategies such as translation, interpretation, and creative translation are required. Although all four types studied in this paper are somewhat different depending on the translator, all translation strategies were used in a comprehensive way. As a result of the study, all four translation strategies used a strategy of direct translation of Chinese characters when translating geographical namesand names of people. The interpretational translation strategy was used for the translation of vocabulary that requires historical, social, cultural, and geography background interpretation. was utilized. The creative translation strategy was used when translating overlapping issues, political and historically sensitive issues, and issues related to Korean pronunciation and grammar. Based on the results of this study, it is expected that translation strategy research on various Chinese translations of Korean modern literature as well as various Chinese translations of Park Wan-seo will be expanded.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.43-54
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• 2022

Simultaneous translation is online decoding to translates with only subsentence. The goal of simultaneous translation research is to improve translation performance against delay. For this reason, most studies find trade-off performance between delays. We studied the experiments of the fixed policy-based simultaneous translation in Korean. Our experiments suggest that Korean tokenization causes many fragments, resulting in delay compared to other languages. We suggest follow-up studies such as n-gram tokenization to solve the problems.