• 정보과학회 논문지
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• 제44권2호
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• pp.163-170
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• 2017

통계적 기계 번역을 이용한 구어-수화 번역 연구가 활발해짐에도 불구하고 수화 말뭉치의 자원 희소성 문제는 해결되지 않고 있다. 본 연구는 수화 번역의 첫 번째 단계로써 통계적 기계 번역을 이용한 구어-수지 신호 번역에서 말뭉치 자원 희소성으로부터 기인하는 문제점들을 해결할 수 있는 세 가지 전처리 방법을 제안한다. 본 연구에서 제안하는 방법은 1) 구어 문장의 패러프레이징을 통한 말뭉치 확장 방법, 2) 구어 단어의 표제어화를 통한 개별 어휘 출현 빈도 증가 및 구어 표현의 번역 가능성을 향상시키는 방법, 그리고 3) 수지 표현으로 전사되지 않는 구어의 기능어 제거를 통한 구어-수지 표현 간 문장 성분을 일치시키는 방법이다. 서로 다른 특징을 지닌 영어-미국 수화 병렬 말뭉치들을 이용한 실험에서 각 방법론들이 단독으로 쓰일 때와 조합되어 함께 사용되었을 때 모두 말뭉치의 종류와 관계없이 번역 성능을 개선시킬 수 있다는 것을 확인할 수 있었다.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 1997년도 제9회 한글 및 한국어 정보처리 학술대회
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• pp.291-295
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• 1997

본 논문은 복합 단위 정보를 이용하여 모호성을 감소시키고 자연스러운 대역어 정보를 제공할 수 있는 차트파서를 기술한다. 복합 단위 정보를 사용하는 파싱은 태깅과 구문 분석 과정 사이에서 여러 단어들을 하나의 단위로 만들어서 형태론적/구문적 모호성과 파스 트리의 수를 감소시킨다. 우리는 Bottom-up 차트 파싱을 사용하는데, 이는 모호성 있는 태깅 결과가 많을수록 파스 트리의 생성 시간과 수의 증가를 초래하므로 복합 단위를 사용하여 파서에 대한 입력 단어의 수 및 모호성을 감소시켜 안정적인 파싱 결과를 얻을 수 있게 한다. 실험 결과는 복합 단위 정보를 사용한 차트 파싱이 차트들의 크기와 파스 트리의 수를 50%까지 감소시킴을 보여준다.

• 정보처리학회논문지D
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• 제15D권5호
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• pp.647-658
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• 2008

자연어로 작성된 고객의 요구사항은 개발과정에서 모델링 언어로 재작성 된다. 그러나 개발에 참여하는 다양한 계층의 사람들은 모델링 언어로 작성된 요구사항을 이해하지 못하는 경우가 많이 발생한다. 본 논문에서는 REED(REquirement EDitor)로 작성된 요구사항 모델을 자연어로 번역하여 개발에 참여하는 모든 계층의 사람들이 요구사항 모델을 이해할 수 있도록 도와주는 방안을 제시한다. 제시한 방법은 3단계로 구성되어 있다. 1단계 IORT(Input-Output Relation Tree) 생성, 2단계 RTT(Requirement Translation Tree) 생성, 3단계 자연어로 번역의 단계를 거친다.

• ETRI Journal
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• 제45권1호
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• pp.18-27
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• 2023

We present an English-Korean speech translation corpus, named EnKoST-C. End-to-end model training for speech translation tasks often suffers from a lack of parallel data, such as speech data in the source language and equivalent text data in the target language. Most available public speech translation corpora were developed for European languages, and there is currently no public corpus for English-Korean end-to-end speech translation. Thus, we created an EnKoST-C centered on TED Talks. In this process, we enhance the sentence alignment approach using the subtitle time information and bilingual sentence embedding information. As a result, we built a 559-h English-Korean speech translation corpus. The proposed sentence alignment approach showed excellent performance of 0.96 f-measure score. We also show the baseline performance of an English-Korean speech translation model trained with EnKoST-C. The EnKoST-C is freely available on a Korean government open data hub site.

• International Journal of Computer Science & Network Security
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• 제23권3호
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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.

• 한국언어정보학회지:언어와정보
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• 제8권1호
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• pp.101-116
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• 2004

This paper proposes a statistical model for the translation of prepositions in English-Korean machine translation. In the proposed model, statistical information acquired from unlabeled Korean corpora is used to choose the best translation from several possible translations. Such information includes functional word-verb co-occurrence information, functional word-verb distance information, and noun-postposition co-occurrence information. The model was evaluated with 443 sentences, each of which has a prepositional phrase, and we attained 71.3% accuracy.

• 영어어문교육
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• 제3호
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• pp.231-248
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• 1997

With the trend of globalization more people are absorbing in the English learning programs. Not a few attend even the English-Korean translation training course to be semi-professional translators, but we English teachers have already experienced that it is not so easy to translate any language into another, and that it is far more difficult to translate poetry. Much time has been devoted to investigating the problems of translating poetry than any other mode. Poetry translation theory is concerned with the problem of faithfulness to the original poetry. To be a good translator we must fully understand the sound and sense of the original work. But when in translating English poetry into Korean we feel keenly our limits of understanding the sound and style of English poetry, and of expressing them into Korean. Even our sense-oriented translation is far from satisfactory. We often make quite a few mistranslation. Another immediate problem is that of alternation between word-for-word translation and free translation method, but first of all, we should have a perfect knowledge and understanding in English, and a good command of our mother tongue. We should also have a sound interpretation ability because poetry translation is based on the interpretation of the original, and on the shaping of that interpretation. Some doubts have been raised over the feasibility of poetry translation. They say it is not possible to combine in another language the emotion, the form, the style, the musical devices of English poetry. Yet the art of translation has been practiced everywhere in the world. Through this art we can share our experience and culture with foreigners and theirs with us.

• 한국정보처리학회논문지
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• 제7권3호
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• pp.756-765
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• 2000

In this paper, a korean text to sign language translation system is designed and implemented for the hearing impaired people to learn letters and to have a conversation with normal people. We adopt the direct method for machine translation which uses morphological analysis and the dictionary search. And we define the necessary sign language dictionaries. Based on this processes, the system translate korean sentences to sign language moving picture. The proposed dictionaries are composed of the basic sign language dictionary, the compound sing language dictionary, and the resemble sign language dictionary. The basic sign language dictionary includes basic symbols and moving pictures of korean sign language. The compound sing language dictionary is composed of key-words of basic sign language. In addition, we offered the similar letters at the resemble sign language dictionary. The moving pictures of searched sign symbols are displayed on a screen in GIF formats by continuous motion of sign symbols or represented by the finger spelling based on the korean code analysis. The proposed system can provide quick sign language search and complement the lack of sign languages in the translation process by using the various sign language dictionaries which are characterized as korean sign language. In addition, to represent the sign language using GIF makes it possible to save the storage space of the sign language. In addition, to represent the sign language using GIF makes it possible to save storage space of the sign language dictionary.

• 한국언어정보학회지:언어와정보
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• 제18권1호
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• pp.77-97
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• 2014

Multilingual machine translation means the machine translation that is for more than two languages. Common transfer means the transfer in which we can reuse the transfer rules among similar languages according to linguistic typology. Therefore, the multilingual machine translation based on common transfer is the multilingual machine translation that can share the transfer rules among languages with similar linguistic typology. This paper describes the linguistic modeling for multilingual machine translation based on common transfer under development. This linguistic modeling consists of the linguistic devices such as 1) multilingual common Part-of-Speech set, 2) multilingual common transfer format, 3) multilingual common transfer chunking, and 4) multilingual common transfer rules based on linguistic typology. Validity of this linguistic modeling for multilingual machine translation is shown in the simulation. The multilingual machine translation system based on common transfer including Korean, English, Chinese, Spanish, and French will be developed till 2018.

• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 2002년도 Language, Information, and Computation Proceedings of The 16th Pacific Asia Conference
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• pp.147-156
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• 2002

Aligned parallel corpora have proved very useful in many natural language processing tasks, including statistical machine translation and word sense disambiguation. In this paper, we describe an alignment technique for extracting transfer mapping from the parallel corpus. During building our system and data collection, we observe that there are three types of translation approaches can be used. We especially focuses on Traditional Chinese and Simplified Chinese text lexical translation and a method for extracting transfer mappings for machine translation.