• Proceedings of the Korean Society for Language and Information Conference
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• 1995.02a
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• pp.133-138
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• 1995

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.75-83
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• 2018

Multicultural family members have difficulty in educating their children due to language differences. In order to solve these difficulties, it is necessary to provide smart translation services that enable them easily and quickly access real-life vocabularies. However, the current automatic translation technology is being developed in dominant languages such as English, Chinese, and Japanese. There are also limitations to translating special-purpose terms such as documents of schools and instructions of public institutions. In this study, we propose a real-time automatic word translation service for multicultural family members who understand beginner level Korean. The service automatically analyzes the semantics of each word in the Korean sentences and provides a word-by-word translation. This study includes semantic analysis research for Korean language, building multilingual translation knowledge, and fusion study of language education. We evaluated the word translation service for migrant women from Vietnam and Japan and obtained meaningful evaluation results.

• Annual Conference on Human and Language Technology
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• 2017.10a
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• pp.184-189
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• 2017

With the advent of robust deep learning method, Neural machine translation has recently become a dominant paradigm and achieved adequate results in translation between popular languages such as English, German, and Spanish. However, its results in under-resourced languages Korean and Vietnamese are still limited. This paper reports an attempt at constructing a bidirectional Korean-Vietnamese Neural machine translation system with the supporting of Korean analysis tool - UTagger, which includes morphological analyzing, POS tagging, and WSD. Experiment results demonstrate that UTagger can significantly improve translation quality of Korean-Vietnamese NMT system in both translation direction. Particularly, it improves approximately 15 BLEU scores for the translation from Korean to Vietnamese direction and 3.12 BLEU scores for the reverse direction.

• Journal of the Korean Society for Library and Information Science
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• v.43 no.1
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• pp.313-332
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• 2009

Cross-language text categorization(CLTC) can classify documents automatically using training set from other language. In this study, collections appropriated for CLTC were extracted from KTSET. Classification performance of various CLTC methods were compared by SVM classifier using machine translation. Results showed that the classification performance in the order of poly-lingual training method, training-set translation and test-set translation. However, training-set translation could be regarded as the most useful method among CLTC, because it was efficient for machine translation and easily adapted to general environment. On the other hand, low performance was shown to be due to the feature reduction or features with no subject characteristics, which occurred in the process of machine translation of CLTC.

• Annual Conference on Human and Language Technology
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• 1996.10a
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• pp.479-483
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• 1996

본 논문은 구운 분석의 검색 영역 축소를 통한 구문 분석기의 성능 향상을 목적으로 connectionism을 이용한 부분 구문 인식기의 설계와 구현을 기술한다. 본 부분 구문 인식기는 형태소 분석된 문장으로부터 명사-주어부와 술어부를 인식함으로써 전체 검색 영역을 여러 부분으로 나누어 구문 분석문제를 축소시키는 것을 목적으로 하고 있다. Connectionist 모델은 입력층과 출력층으로 구성된 개선된 퍼셉트론 구조이며, 입/출력층 사이의 노드들을, 입력층 사이의 노드들을 연결하는 연결 강도(weight)가 존재한다. 명사-주어부 및 술어부 구문 태그를 connectionist 모델에 적용하며, 학습 알고리즘으로는 개선된 백프로퍼게이션 학습 알고리즘을 사용한다. 부분 구문 인식 실험은 112개 문장의 학습 코퍼스와 46개 문장의 실험 코퍼스에 대하여 85.7%와 80.4%의 정확한 명사-주어부 및 술어부 인식을, 94.6%와 95.7%의 명사-주어부와 술어부 사이의 올바른 경계 인식을 보여준다.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.206-212
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• 2021

Society is developing more and more, and communication methods are developing in many ways. However, developed communication is a way for the non-disabled and has no effect on the deaf. Therefore, in this paper, a CNN-based sign language translation program is designed and implemented to help deaf people communicate. Sign language translation programs translate sign language images entered through WebCam according to meaning based on data. The sign language translation program uses 24,000 pieces of Korean vowel data produced directly and conducts U-Net segmentation to train effective classification models. In the implemented sign language translation program, 'ㅋ' showed the best performance among all sign language data with 97% accuracy and 99% F1-Score, while 'ㅣ' showed the highest performance among vowel data with 94% accuracy and 95.5% F1-Score.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.461-467
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• 2017

As the number of smart devices increases, e-book contents and services are proliferating. However, the text based e-book is difficult for a hearing-impairment person to understand. In this paper, we developed an android based application in which we can choose an e-book text file and each sentence is translated to sign-language elements which are shown in videos that are retrieved from the sign-language contents server. We used the korean sentence to sign-language translation algorithm based on the morpheme analysis. The proposed translation algorithm consists of 3 stages. Firstly, some elements in a sentence are removed for typical sign-language usages. Secondly, the tense of the sentence and the expression alteration are applied. Finally, the honorific forms are considered and word positions in the sentence are revised. We also proposed a new method to evaluate the performance of the translation algorithm and demonstrated the superiority of the algorithm through the translation results of 100 reference sentences.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.1 no.1
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• pp.23-35
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• 1983

In its global meaning language translation refers to the process whereby a program which is executable in one computer can be executed in another computer directly to obtain the same result. There are four different ways of approaching translation. The first way is translation by a Translator or a Compier, the second way is Interpretation, the third way is Simulation, the last way is Emulation. This paper introduces the M-C Translator which was designed as the first way of translation. The MUSS 80 language (the subsystem of the UNIVAC Solid State 80 S-4 assembly language system) was chosen as the source language which includes forty-three instructions, using the CYBER COMPASS as the object language. The M-C translator is a two pass translator and is a two pas translator and es written in Fortran Extended language. For this M-C Translation, seven COMPASS subroutines and a set of thirty-five macros were prepared. Each executable source instruction corresponds to a macro, so it will be a macro instruction within the object profram. Subroutines are used to retain and handle the source data representation the same way in the object program as in the source system, and are used to convert the decimal source data into the equivalent binary result into the equivalent USS-80digits before and after arithmetic operations. The source instructions can be classified into three categories. First, therd are some instructions which are meaningless in the object system and are therefore unnecessary to translate, and the remaining instructions should be translated. Second, There are some instructions are required to indicate dual address portions. Third, there are Three instructions which have overflow conditions, which are lacking in the remaining instructions. The construction and functions of the M-C Translator, are explained including some of the subroutines, and macros. The problems, difficulties and the method of solving them, and easier features on this translation are analysed. The study of how to save memory and time will be continued.

• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.183-188
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• 2012

One of the major challenge for retrieval performance is the word mismatch between user's queries and documents in information retrieval. To solve the word mismatch problem, we propose a retrieval model based on the degree of association of query concept and word translation probabilities in translation-based model. The word translation probabilities are calculated based on the set of a sentence and its succeeding sentence pair. To validate the proposed method, we experimented on TREC AP test collection. The experimental results show that the proposed model achieved significant improvement over the language model and outperformed translation-based language model.

• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2361-2368
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• 1998

This paper analyzes Korean spoken language and describes the machine translation o[ Korean to-English spoken language based on semantic patterns, In Korean-to-English machine translation. ambiguity of Korean sentence analysis using syntactic information can be resolved by semantic patterns, Therefore, for machine translation of spoken language, we estabilish the system based on semantic patterns extracted from Korean scheduling domain, This system obtains the robustness by skip ability of syllables in analysis of Korean sentence and we add options to semantic patterns in order to reduce pattern numbers, The data used [or the experiment are scheduling domain and performance of Korean-to-English translation is 88%.