• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.71-76
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• 2006

To obtain a correctly translated sentence in a machine translation system, we must select target words that not only reflect an appropriate meaning in a source sentence but also make a fluent sentence in a target language. This paper points out that a source language word has various senses and each sense can be mapped into multiple target words, and proposes a new translation disambiguation method based on this 'word-to-sense and sense-to-word' relationship. In my method target words are chosen through disambiguation of a source word sense and selection of a target word. Most of translation disambiguation methods are based on a 'word-to-word' relationship that means they translate a source word directly into a target wort so they require complicate knowledge sources that directly link a source words to target words, which are hard to obtain like bilingual aligned corpora. By combining two sub-problems for each language, knowledge for translation disambiguation can be automatically extracted from knowledge sources for each language that are easy to obtain. In addition, disambiguation results satisfy both fidelity and intelligibility because selected target words have correct meaning and generate naturally composed target sentences.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.487-493
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• 2003

인터넷의 발전으로 국경을 초월한 팀간의 국제적 협업도 기술적으로 가능하게 되었다. 그러나 공용어가 아닌 각자의 모국어를 사용하는 경우 인터넷과 자동기계번역 (Machine Translation)을 활용하여 협업이 가능하도록 하기 위하여는 아직도 해결되어야 말 문제가 많다. 특히 자동기계번역은 특정 언어 외의 다양산 언어들간의 번역에서는 아직도 의사소통이 원활하게 이루어지지 않는 수준이다. 본 연구는 상이산 문화적 배경을 가지고 서로 다른 모국어를 사용하는 팀 간의 협업이 현재의 기술 수준으로 어느 정도까지 가능한가 하는 것을, 자동기계번역과 인터넷을 기반으로 고안된 ICSS ([nterrultural Collaboration Support System)를 활용한 실험을 통하여, 시스템과 인간의 상호작용을 중심으로 고찰하고자 하였다.

• Annual Conference on Human and Language Technology
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• 2007.10a
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• pp.228-232
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• 2007

In this paper we propose comparison of both verb and noun endings between Korean and Mongolian languages. It is based on the similarity between two languages which have the same sentence structures and their eomi and josa structure. Korean verb and noun endings match into those of corresponding Mongolian endings. Josa and eomi are classified as a one-to-one, a one-to-many, and a many-to-many cases as well as some abnormal cases. In order to encourage development of Korean to Mongolian machine translation system, this paper would introduce one of the significant units in grammar.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.631-653
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• 2020

Sign language is a natural, visually oriented and non-verbal communication channel between people that facilitates communication through facial/bodily expressions, postures and a set of gestures. It is basically used for communication with people who are deaf or hard of hearing. In order to understand such communication quickly and accurately, the design of a successful sign language translation system is considered in this paper. The proposed system includes object detection and classification stages. Firstly, Single Shot Multi Box Detection (SSD) architecture is utilized for hand detection, then a deep learning structure based on the Inception v3 plus Support Vector Machine (SVM) that combines feature extraction and classification stages is proposed to constructively translate the detected hand gestures. A sign language fingerspelling dataset is used for the design of the proposed model. The obtained results and comparative analysis demonstrate the efficiency of using the proposed hybrid structure in sign language translation.

• Proceedings of the Korean Society for Language and Information Conference
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• 1994.02a
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• pp.153-162
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• 1994

• Proceedings of the Korean Society for Language and Information Conference
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• 1996.02a
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• pp.53-62
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• 1996

• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1792-1802
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• 1996

The analysis of prepositional phrases in English-to Korean machine translation has problem on the PP-attachment resolution, semantic analysis, and acquisition of information. This paper presents an analysis system for prepositional phrases, which solves the problem. The analysis system consists of the PP-attachment resolution hybrid system, semantic analysis system, and semantic feature generator that automatically generates input information. It provides objectiveness in analyzing prepositional phrases with the automatic generation of semantic features. The semantic analysis system enables to generate natural Korean expressions through selection semantic roles of prepositional phrases. The PP-attachment resolution hybrid system has the merit of the rule-based and neural network-based method.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2000.06a
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• pp.350-357
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• 2000

본 논문은 근 몇 년간 꾸준히 진행되어진 중한 기계번역시스템에 대한 연구의 기초 위에서, 뉴스 타이틀 번역이라는 특정 도메인에 초점을 맞추어 언어적 특성을 살펴보고, 중한 언어적 유사성에 기반 한 뉴스 타이틀 번역을 위한 중한 기계번역시스템에 대하여 설명한다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.4
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• pp.466-476
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• 1986

This paper proposes a system that translates the machine independent intermediate micro-programming language(IML) into microcode, using the register allocation algorithm, the microinstruction format and the field information for the target machine emulation on a microprogrammable host machine. The IML, which is for PDP-8 emulation on a microprogrammable hypothsetical 16 bit host machine, is microcoded by the proposed system, and the validity of the algorithm in the proposed system is verified by executing a test program of the target machine on the emulator.

• Annual Conference of KIPS
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• 2009.11a
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• pp.239-240
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• 2009

We live in a flat world in which globalization fosters communication, travel, and trade among more than 150 countries and thousands of languages. To surmount the barriers among these languages, translation is required; Speech-to-Speech translation will automate the process. Thanks to recent advances in Automatic Speech Recognition (ASR), Machine Translation (MT), and Text-to-Speech (TTS), one can now utilize a system to translate a speech of source language to a speech of target language and vice versa in affordable manner. The three phase process establishes that the source speech be transcribed into a (set of) text of the source language (ASR) before the source text is translated into the target text (MT). Finally, the target speech is synthesized from the target text (TTS).