• The Journal of Korean Association of Computer Education
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• v.8 no.2
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• pp.23-32
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• 2005

Educational Programming Language (EPL) should be learner-friendly and easy to use. Dolittle, an object-oriented educational programming language (EPL), offers programming environment which can be programmed in Korean(Hangul). However, since some Dolittle commands are not appropriate to elementary and middle school students, it shows limitations for learners to express programming process. In this paper, we developed a set of 1:n multi-reserved words which are able to program with Korean linguistic characteristics as well as considering learners' differences, preferences, and applicable areas. The conclusion in the paper showed that programming with this 1:n multi-reserved words helped learners concentrate on problem solving regardless of the reserved words.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.523-529
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• 2021

In this paper, we designed and developed an Emotional Speech Synthesis Markup Language (SSML) processor. Multi-speaker emotional speech synthesis technology that can express multiple voice colors and emotional expressions have been developed, and we designed Emotional SSML by extending SSML for multiple voice colors and emotional expressions. The Emotional SSML processor has a graphic user interface and consists of following four components. First, a multi-speaker emotional text editor that can easily mark specific voice colors and emotions on desired positions. Second, an Emotional SSML document generator that creates an Emotional SSML document automatically from the result of the multi-speaker emotional text editor. Third, an Emotional SSML parser that parses the Emotional SSML document. Last, a sequencer to control a multi-speaker and emotional Text-to-Speech (TTS) engine based on the result of the Emotional SSML parser. Based on SSML which is a programming language and platform independent open standard, the Emotional SSML processor can easily integrate with various speech synthesis engines and facilitates the development of multi-speaker emotional text-to-speech applications.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.63-68
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• 2022

There are 395,789 people with hearing impairment in Korea, according to the 2021 Disability Statistics Annual Report by the Korea Institute for the Development of Disabled Persons. These people are experiencing a lot of inconvenience through hearing impairment, and many studies related to recognition and translation of Korean sign language are being conducted to solve this problem. In sign language recognition and translation research, collecting sign language data has many difficulties because few people use sign language professionally. In addition, most of the existed data is sign language data taken from the front of the speaker. To solve this problem, in this paper, we designed and developed a storage system that can collect sign language data based on multi-view points in real-time, rather than a single point, and store and manage it with high usability.

• Journal of KIISE:Software and Applications
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• v.37 no.1
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• pp.19-28
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• 2010

Recently, various home appliances are inter connected in wired/wireless network to provide a single service, but their interfaces are not uniformly integrated. In order to get a service in such an environment, users have to figure out how to control each appliance and the way of combining its functions with others. Even worse to the users, many buttons are barely used to control the complicated functions of the appliances on the remote controllers, and controllers have very similar shapes in each other. In this paper, based on the definitions of a task as a unit of services provided in the environment of multi-connected appliances, we propose a markup language for home appliances, called HAML (Home Appliance Markup Language), for generating task-based user interfaces to help controlling multi-connected appliances as one pleases. The proposed method generates interfaces by gathering the buttons frequently used and necessary for tasks, and provides automatic settings of multi-connected appliances. The proposed method is verified with an analysis of scenarios and usability tests.

• The Korean Journal of Community Living Science
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• v.27 no.1
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• pp.95-108
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• 2016

The objectives of this study are to analyze the characteristics of multi-cultural families in rural areas and to classify their types by applying multi-variate techniques and cluster analyses. Data for the study were obtained by a surveying 120 married migrant females in rural areas of Chungchengnam-do, South Korea. By utilizing the factor analysis to analyze the characteristics of multi-cultural families, 16 basic variables related to these female subjects were categorized into 6 factors: 'marriage length and age', 'language skill of migrant female', 'language skill of husband', 'family satisfaction', 'income and education', and 'general living satisfaction in Korea with remittance'. By appling the cluster analysis, multi-cultural families in rural areas were divided into the following 5 types: 'stable settlement', 'average but stagnant', 'below average yet positive', 'high- income with little communication', and 'young low-income'. In all types, it is strongly recommended to develop various programs regarding vocational education for the migrant females in order to increase their economic opportunities as well as social status.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2006.06a
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• pp.103-109
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• 2006

XML(extensible Markup Language)이 1996년 등장한 이후, 기존의 정보를 XML 기반으로 나타내기 위한 연구가 활발하게 이루어지고 있다. 언어자원(language Resource)과 관련된 분야는 80년대부터 그 연구가 있었으나, XML의 등장 이후, 보다 다양하고 특화된 영역의 정보를 구조화하기 위한 연구결과가 최근 소개되기 시작하였다. 본 연구에서는 이러한 분야 중 전자사전을 표식(markup)하는 XML기반 표준언어인 LEXml(Presentation/Representation of Entries in Dictionaries: LEXml)에 대하여 살펴보고, 기존에 XML로 구축된 전자사전을 LEXml로 변환하여, 그 구조의 확장성과 유효성을 검증할 것이다. 기반자료로써 2000년도에 구축된 MultiDICO의 불어 정보를 이용하였다. 이를 위해 MultiDICO의 XML문서 구조와 LEXml 구조 사이의 각 요소(element)별 대응표를 만들었으며, 이를 바탕으로 XSL(Extensible Style sheet Language)를 작성하였다. 본 연구결과 LEXml이 기존에 구축된 전자사전들을 표식하는데 어려움이 없을 뿐만 아니라, 기계가독성을 높일 수 있는 구조적 유연성이 매우 높은 것을 확인할 수 있었다.

• Annual Conference on Human and Language Technology
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• 2021.10a
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• pp.540-543
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• 2021

본 논문에서는 Multi-Head Attention 대신 Spatial Gating Unit을 사용하는 GMLP[1]에 작은 Attention 신경망을 추가한 모델을 구성하여 뉴스와 위키피디아 데이터로 사전학습을 실시하고 한국어 다운스트림 테스크(감성분석, 개체명 인식)에 적용해 본다. 그 결과, 감성분석에서 Multilingual BERT보다 0.27%높은 Accuracy인 87.70%를 보였으며, 개체명 인식에서는 1.6%높은 85.82%의 F1 Score를 나타내었다. 따라서 GMLP가 기존 Transformer Encoder의 Multi-head Attention[2]없이 SGU와 작은 Attention만으로도 BERT[3]와 견줄만한 성능을 보일 수 있음을 확인할 수 있었다. 또한 BERT와 추론 속도를 비교 실험했을 때 배치사이즈가 20보다 작을 때 BERT보다 1에서 6배 정도 빠르다는 것을 확인할 수 있었다.

• Journal of English Language & Literature
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• v.56 no.6
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• pp.1163-1190
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• 2010

Korean EFL learners' stylistic sensitivity was examined through the two types of letter writing, professional and personal. The base of comparison with the English native speakers' stylistic sensitivity was the linguistic style markers that were statistically found by Biber's (1988) multi-dimensional model of variation of English language. The main finding was that Korean university students were sensitive to stylistic difference in the correct direction, though their linguistic repertoire was limited to the easy and simple linguistic features. Also, the learners were skewed in the involved style in both types of the letters unlike the native speakers and it was interpreted as due to the general developmental direction from informal to formal linguistic style. Learners were also skewed in the explicit style in both types of letters unlike the native speakers and it was interpreted as due to the learners' heavy reliance on one particular linguistic feature. As a whole, the learners' stylistic sensitivity heavily relied on the small number of linguistic features that they have already acquired, which happen to be simple and basic linguistic features.

• Annual Conference on Human and Language Technology
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• 2017.10a
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• pp.103-107
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• 2017

한국어 형태소 분석 및 구구조 구문 분석은 한국어 자연어처리에서 난이도가 높은 작업들로서 최근에는 해당 문제들을 출력열 생성 문제로 바꾸어 sequence-to-sequence 모델을 이용한 end-to-end 방식의 접근법들이 연구되었다. 한국어 형태소 분석 및 구구조 구문 분석을 출력열 생성 문제로 바꿀 시 해당 출력 결과는 하나의 열로서 합쳐질 수가 있다. 본 논문에서는 sequence-to-sequence 모델을 이용하여 한국어 형태소 분석 및 구구조 구문 분석을 동시에 처리하는 모델을 제안한다. 실험 결과 한국어 형태소 분석과 구구조 구문 분석을 동시에 처리할 시 형태소 분석이 구구조 구문 분석에 영향을 주는 것을 확인 하였으며, 구구조 구문 분석 또한 형태소 분석에 영향을 주어 서로 영향을 줄 수 있음을 확인하였다.

• Annual Conference on Human and Language Technology
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• 2017.10a
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• pp.56-59
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• 2017

CNN(Convolutional Neural Network)을 이용하여 발화 주제 다중 분류 task를 multi-labeling 방법과, cluster 방법을 이용하여 수행하고, 각 방법론에 MSE(Mean Square Error), softmax cross-entropy, sigmoid cross-entropy를 적용하여 성능을 평가하였다. Network는 음절 단위로 tokenize하고, 품사정보를 각 token의 추가한 sequence와, Naver DB를 통하여 얻은 named entity 정보를 입력으로 사용한다. 실험결과 cluster 방법으로 문제를 변형하고, sigmoid를 output layer의 activation function으로 사용하고 cross entropy cost function을 이용하여 network를 학습시켰을 때 F1 0.9873으로 가장 좋은 성능을 보였다.