• Title/Summary/Keyword: 언어 융합

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Korean and Multilingual Language Models Study for Cross-Lingual Post-Training (XPT) (Cross-Lingual Post-Training (XPT)을 위한 한국어 및 다국어 언어모델 연구)

  • Son, Suhyune;Park, Chanjun;Lee, Jungseob;Shim, Midan;Lee, Chanhee;Park, Kinam;Lim, Heuiseok
    • Journal of the Korea Convergence Society
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    • v.13 no.3
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    • pp.77-89
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    • 2022
  • It has been proven through many previous researches that the pretrained language model with a large corpus helps improve performance in various natural language processing tasks. However, there is a limit to building a large-capacity corpus for training in a language environment where resources are scarce. Using the Cross-lingual Post-Training (XPT) method, we analyze the method's efficiency in Korean, which is a low resource language. XPT selectively reuses the English pretrained language model parameters, which is a high resource and uses an adaptation layer to learn the relationship between the two languages. This confirmed that only a small amount of the target language dataset in the relationship extraction shows better performance than the target pretrained language model. In addition, we analyze the characteristics of each model on the Korean language model and the Korean multilingual model disclosed by domestic and foreign researchers and companies.

Verbal Violence Type in Operating Room Nurses, Fusion Study on Emotional Response and Coping (수술실 간호사의 언어폭력유형, 정서적 반응과 대처에 대한 융합연구)

  • Oh, Suk-Hee;Sun, Jeong-Ju;Kang, Hee-Sun
    • Journal of Convergence for Information Technology
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    • v.9 no.8
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    • pp.53-62
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    • 2019
  • This study is a descriptive study to investigate the relationship between verbal violence type, emotional response and coping in the operating room nurse. The subjects of the study were 400 nurses working in 20 general hospitals and 372 nurses in the operating room. As a result of the analysis, it was found that the perpetrators of the verbal violence experienced by the subject were physicians, direct supervisors, and more than half of the subjects were considering the transition. The most frequent cases of language violence were when the equipment was inoperable or not used during surgery, There were significant differences in verbal violence experience according to marriage, clinical career, and work style. Language violence emotional response showed significant difference with gender, position and coping, age, academic background, clinical career, and position. There was a significant correlation between experience of verbal violence and emotional response, emotional response and coping. Therefore, the results of this study will contribute to the development of coping strategies and prevention education programs.

A Study on use of Para-languages affecting Choral Communication -focused on diction of Korean choral music- (합창 커뮤니케이션에 영향을 미치는 유사언어의 활용에 관한 연구 -한국어 합창 딕션을 중심으로-)

  • Kim, Hyung-il
    • Journal of the Korea Convergence Society
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    • v.8 no.6
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    • pp.299-309
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    • 2017
  • The study was aimed at finding an effective use of para-languages, which are important to communicate the meaning of the korean choral music. Para-language is a nonverbal communication that contributes to the delivery of a more expressive language. In choral music, vocalization and diction are important para-languages. Until now, the conductors emphasized vocalization rathe than diction while focusing musical expression in chorus. However, vocalization and diction are not distinct. This study suggested effective choral vocalization and diction technique through the convergence of experience as conductor and knowledge of communication theory.

Production of Media Art using OpenCV (OpenCV를 이용한 미디어 아트 제작)

  • Lee, MyounJae
    • Journal of the Korea Convergence Society
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    • v.7 no.4
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    • pp.173-180
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    • 2016
  • OpenCV is a programming language used in digital image processing and computer vision. In this study, look at media arts made using OpenCV programming language and find out about the utilization possibilities. To this end, the first, look at OpenCV functions that are frequently used in media art, the examples of utilizing the functions. The second, discuss media arts using OpenCV. focused on the OpenCV functions, programming language for an production of media art. The third, analyze features of media arts using OpenCV, mainly focused on the functions and programming languages. The study may provide guidance to the artists to produce a media art using the OpenCV or programming language.

The Effect of Service Provider Nonverbal Attributes on Customer Evaluation in Service Recovery Stage (서비스 회복 단계에서, 접점 서비스 제공자의 비구두적 요인(Nonverbal Attributes)이 고객평가에 미치는 영향)

  • Yeo, Chan-Koo
    • Journal of the Korea Convergence Society
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    • v.4 no.3
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    • pp.7-13
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    • 2013
  • The objective of this research is to find out the effect of service provider nonverbal attributes on customer evaluation in service recovery stage. Results showed that first, the better kinesics of service provider, the more satisfaction in service recovery stage. Second, the better service providers have physical appearance, the more revisit intention. But both the kinesics and physical appearance have not an effect on recommendation intention. This paper discussed theoretical and practical focusing on nonverbal attributes of service providers.

Korean-English Non-Autoregressive Neural Machine Translation using Word Alignment (단어 정렬을 이용한 한국어-영어 비자기회귀 신경망 기계 번역)

  • Jung, Young-Jun;Lee, Chang-Ki
    • Annual Conference on Human and Language Technology
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    • 2021.10a
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    • pp.629-632
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    • 2021
  • 기계 번역(machine translation)은 자연 언어로 된 텍스트를 다른 언어로 자동 번역 하는 기술로, 최근에는 주로 신경망 기계 번역(Neural Machine Translation) 모델에 대한 연구가 진행되었다. 신경망 기계 번역은 일반적으로 자기회귀(autoregressive) 모델을 이용하며 기계 번역에서 좋은 성능을 보이지만, 병렬화할 수 없어 디코딩 속도가 느린 문제가 있다. 비자기회귀(non-autoregressive) 모델은 단어를 독립적으로 생성하며 병렬 계산이 가능해 자기회귀 모델에 비해 디코딩 속도가 상당히 빠른 장점이 있지만, 멀티모달리티(multimodality) 문제가 발생할 수 있다. 본 논문에서는 단어 정렬(word alignment)을 이용한 비자기회귀 신경망 기계 번역 모델을 제안하고, 제안한 모델을 한국어-영어 기계 번역에 적용하여 단어 정렬 정보가 어순이 다른 언어 간의 번역 성능 개선과 멀티모달리티 문제를 완화하는 데 도움이 됨을 보인다.

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The Verification of the Transfer Learning-based Automatic Post Editing Model (전이학습 기반 기계번역 사후교정 모델 검증)

  • Moon, Hyeonseok;Park, Chanjun;Eo, Sugyeong;Seo, Jaehyung;Lim, Heuiseok
    • Journal of the Korea Convergence Society
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    • v.12 no.10
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    • pp.27-35
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    • 2021
  • Automatic post editing is a research field that aims to automatically correct errors in machine translation results. This research is mainly being focus on high resource language pairs, such as English-German. Recent APE studies are mainly adopting transfer learning based research, where pre-training language models, or translation models generated through self-supervised learning methodologies are utilized. While translation based APE model shows superior performance in recent researches, as such researches are conducted on the high resource languages, the same perspective cannot be directly applied to the low resource languages. In this work, we apply two transfer learning strategies to Korean-English APE studies and show that transfer learning with translation model can significantly improves APE performance.

A Study on the Instructional Model utilizing Scratch for Introductory Programming Classes of SW-Major Students (SW전공자 프로그래밍 입문 수업의 스크래치 활용 수업 모형 연구)

  • KO, Kwangil
    • Convergence Security Journal
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    • v.18 no.2
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    • pp.59-67
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    • 2018
  • The programming language is a core education area of software that is becoming increasingly important in the age of the fourth industrial revolution, but it requires mathematical knowledge and logical thinking skills, so that many local private university and college students with low basic skills are having difficulties learning it. This problem occasionally causes SW-major students to lose interest and confidence in their majors during the introductory course of programming languages; making them change their majors, or give up their studies. In this study, we designed an instructional model using Scratch for educating C-language which is a typical programming introductory language. To do this, we analyzed the concepts that can be trained by Scratch among the programming concepts supported by C-language, and developed the examples of Scratch for exercising the concepts. In addition, we designed an instructional model, by which the programming concepts are first learned through Scratch and then C-language is taught, and conducted an experiment on the SW-major freshman students of a local private university to verify the effectiveness of the model. In the situation where SW education is becoming common, we expect that this study will help programming language education of security IT students.

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Korean sentence spacing correction model using syllable and morpheme information (음절과 형태소 정보를 이용한 한국어 문장 띄어쓰기 교정 모델)

  • Choi, Jeong-Myeong;Oh, Byoung-Doo;Heo, Tak-Sung;Jeong, Yeong-Seok;Kim, Yu-Seop
    • Annual Conference on Human and Language Technology
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    • 2020.10a
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    • pp.141-144
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    • 2020
  • 한국어에서 문장의 가독성이나 맥락 파악을 위해 띄어쓰기는 매우 중요하다. 또한 자연 언어 처리를 할 때 띄어쓰기 오류가 있는 문장을 사용하면 문장의 구조가 달라지기 때문에 성능에 영향을 미칠 수 있다. 기존 연구에서는 N-gram 기반 통계적인 방법과 형태소 분석기를 이용하여 띄어쓰기 교정을 해왔다. 최근 들어 심층 신경망을 활용하는 많은 띄어쓰기 교정 연구가 진행되고 있다. 기존 심층 신경망을 이용한 연구에서는 문장을 음절 단위 또는 형태소 단위로 처리하여 교정 모델을 만들었다. 본 연구에서는 음절과 형태소 단위 모두 모델의 입력으로 사용하여 두 정보를 결합하여 띄어쓰기 교정 문제를 해결하고자 한다. 모델은 문장의 음절과 형태소 시퀀스에서 지역적 정보를 학습할 수 있는 Convolutional Neural Network와 순서정보를 정방향, 후방향으로 학습할 수 있는 Bidirectional Long Short-Term Memory 구조를 사용한다. 모델의 성능은 음절의 정확도와 어절의 정밀도, 어절의 재현율, 어절의 F1 score를 사용해 평가하였다. 제안한 모델의 성능 평가 결과 어절의 F1 score가 96.06%로 우수한 성능을 냈다.

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