• Title/Summary/Keyword: Computer Language

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Development and Application of Robot Contents for Symbolic Vocal Language Learning of Young Children (상징적 음성언어 교육을 위한 유아 로봇 콘텐츠 개발 및 적용)

  • Kim, Jeong-Ho;Han, Jeong-Hye;Kim, Dong-Ho
    • Journal of The Korean Association of Information Education
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    • v.13 no.2
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    • pp.205-214
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    • 2009
  • The vocal language which is a symbolic vocal language described external sounds or expressed shape of things in nature, phenomenon, movement, shape of state provided images which can be envisioned in minds and created the mood for the whole writings. As the instructive ways of symbolic vocal language, the activities which refrain one-way translation for lexicon definition and stimulate the thoughts of students and interesting activities such as songs and comic books which students can understand by themselves are needed. Therefore, in this study, these symbolic vocal language is to be developed as the contents of robot for Symbolic Vocal language learning activities and after study activities, the possibility of using robot for education is to be reviewed, comparing changes in definitive areas and achievement after study activities. After the Symbolic Vocal language learning activities using robot and computer, as results of testing three achievement types of words simulated sound, shape, and movement, in study on words simulating sound and shape there was no significant difference. But The study activities simulating words used robot showed significant difference in terms of interest, confidence, and understanding.

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Measuring and Applying the Self-efficacy in Computer Programming Education (컴퓨터 프로그래밍 언어 교육에서 자기 효능감 척도 개발 및 적용)

  • Kim, Kapsu
    • Journal of The Korean Association of Information Education
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    • v.18 no.1
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    • pp.111-120
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    • 2014
  • Information and knowledge society in the 21st century computer education is very important. Until now, much research on computer applications in education and training in computer literacy are a lot of self-efficacy scales have been developed. However, the development of students' creativity and reasoning to computer literacy education is more important than education is a computer programming language. And self-efficacy for teaching computer programming language developed measures insufficient. Therefore, in this study, self-efficacy for teaching computer programming language developed scale. This measure is a computer that can be programmed to target elementary school students were investigated. The results of computer programming education for elementary school children who are higher in the self-efficacy. The results of this study are that elementary school students when teaching computer programming that is very reasonable results.

Sign Language Translation Using Deep Convolutional Neural Networks

  • Abiyev, Rahib H.;Arslan, Murat;Idoko, John Bush
    • 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.

Development of Foreign Language Fluency Diagnosis Tools For Brain Scientific Language Learning (뇌공학적 외국어 학습을 위한 외국어 능숙도 진단 도구 개발)

  • Lee, Sae-Byeok;Lee, Won-Gyu;Kim, Hyeon-Cheol;Jung, Soon-Young;Lim, Heui-Seok
    • The Journal of Korean Association of Computer Education
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    • v.13 no.1
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    • pp.37-44
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    • 2010
  • Recently, the scientific approach to brain engineering is actively being made for effective foreign language learning and diagnosis. In order to supplement the problem of preexistence paper exam, the study aimed to develop a tool for foreign language fluency diagnosis which based on brain engineering. The proposed tools in the paper indirectly measure the aspects of brain information processing by testing learners' 3 abilities of linguistic memory, comprehension, and language production in 5 different ways.

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Extended pivot-based approach for bilingual lexicon extraction

  • Seo, Hyeong-Won;Kwon, Hong-Seok;Kim, Jae-Hoon
    • Journal of Advanced Marine Engineering and Technology
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    • v.38 no.5
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    • pp.557-565
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    • 2014
  • This paper describes the extended pivot-based approach for bilingual lexicon extraction. The basic features of the approach can be described as follows: First, the approach builds context vectors between a source (or target) language and a pivot language like English, respectively. This is the same as the standard pivot-based approach which is useful for extracting bilingual lexicons between low-resource languages such as Korean-French. Second, unlike the standard pivot-based approach, the approach looks for similar context vectors in a source language. This is helpful to extract translation candidates for polysemous words as well as lets the translations be more confident. Third, the approach extracts translation candidates from target context vectors through the similarity between source and target context vectors. Based on these features, this paper describes the extended pivot-based approach and does various experiments in a language pair, Korean-French (KR-FR). We have observed that the approach is useful for extracting the most proper translation candidate as well as for a low-resource language pair.

Validity of Language-Based Algorithms Trained on Supervisor Feedback Language for Predicting Interpersonal Fairness in Performance Feedback

  • Jisoo Ock;Joyce S. Pang
    • Asia pacific journal of information systems
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    • v.33 no.4
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    • pp.1118-1134
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    • 2023
  • Previous research has shown that employees tend to react more positively to corrective feedback from supervisors to the extent they perceive that they were treated with empathy, respect, and concern towards fair interpersonal treatment in receiving the feedback information. Then, to facilitate effective supervisory feedback and coaching, it would be useful for organizations to monitor the contents of feedback exchanges between supervisors and employees to make sure that supervisors are providing performance feedback using languages that are more likely to be perceived as interpersonally fair. Computer-aided text analysis holds potential as a useful tool that organizations can use to efficiently monitor the quality of the feedback messages that supervisors provide to their employees. In the current study, we applied computer-aided text analysis (using closed-vocabulary text analysis) and machine learning to examine the validity of language-based algorithms trained on supervisor language in performance feedback situations for predicting human ratings of feedback interpersonal fairness. Results showed that language-based algorithms predicted feedback interpersonal fairness with reasonable level of accuracy. Our findings provide supportive evidence for the promise of using employee language data for managing (and improving) performance management in organizations.

Bilingual lexicon induction through a pivot language

  • Kim, Jae-Hoon;Seo, Hyeong-Won;Kwon, Hong-Seok
    • Journal of Advanced Marine Engineering and Technology
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    • v.37 no.3
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    • pp.300-306
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    • 2013
  • This paper presents a new method for constructing bilingual lexicons through a pivot language. The proposed method is adapted from the context-based approach, called the standard approach, which is well-known for building bilingual lexicons using comparable corpora. The main difference between the standard approach and the proposed method is how to represent context vectors. The former is to represent context vectors in a target language, while the latter in a pivot language. The proposed method is very simplified from the standard approach thereby. Furthermore, the proposed method is more accurate than the standard approach because it uses parallel corpora instead of comparable corpora. The experiments are conducted on a language pair, Korean and Spanish. Our experimental results have shown that the proposed method is quite attractive where a parallel corpus directly between source and target languages are unavailable, but both source-pivot and pivot-target parallel corpora are available.

Real Time Recognition of Finger-Language Using Color Information and Fuzzy Clustering Algorithm

  • Kim, Kwang-Baek;Song, Doo-Heon;Woo, Young-Woon
    • Journal of information and communication convergence engineering
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    • v.8 no.1
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    • pp.19-22
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    • 2010
  • A finger language helping hearing impaired people in communication A sign language helping hearing impaired people in communication is not popular to ordinary healthy people. In this paper, we propose a method for real-time sign language recognition from a vision system using color information and fuzzy clustering system. We use YCbCr color model and canny mask to decide the position of hands and the boundary lines. After extracting regions of two hands by applying 8-directional contour tracking algorithm and morphological information, the system uses FCM in classifying sign language signals. In experiment, the proposed method is proven to be sufficiently efficient.

Comparative Analysis of Statistical Language Modeling for Korean using K-SLM Toolkits (K-SLM Toolkit을 이용한 한국어의 통계적 언어 모델링 비교)

  • Lee, Jin-Seok;Park, Jay-Duke;Lee, Geun-Bae
    • Annual Conference on Human and Language Technology
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    • 1999.10e
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    • pp.426-432
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    • 1999
  • 통계적 언어 모델은 자연어 처리의 다양한 분야에서 시스템의 정확도를 높이고 수행 시간을 줄여줄 수 있는 중요한 지식원이므로 언어 모델의 성능은 자연어 처리 시스템, 특히 음성 인식 시스템의 성능에 직접적인 영향을 준다. 본 논문에서는 한국어를 위한 통계적 언어 모델을 구축하기 위한 다양한 언어 모델 실험을 제시하고 각 언어 모델들 간의 성능 비교를 통하여 통계적 언어 모델의 표준을 제시한다. 또한 형태소 및 어절 단위의 고 빈도 어휘만을 범용 언어 모델에 적용할 때의 적용률을 통하여 언어 모델 구축시 어휘 사전 크기 결정을 위한 기초적 자료를 제시한다. 본 연구는 음성 인식용 통계적 언어 모델의 성능을 판단하는 데 앞으로 큰 도움을 줄 수 있을 것이다.

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A Study on the Natural Language Query System Using Sentence-Pattern (문장패턴을 이용한 자연어 질의 시스템에 대한 연구)

  • Woo, Keun-Sin;Song, Jae-Gwan;Hong, Sung-Woong;Yon, Che-Yong;Park, Chan-Gun
    • Annual Conference on Human and Language Technology
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    • 2003.10d
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    • pp.214-218
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    • 2003
  • 질의응답 시스템은 인터넷과 같은 실용적 환경에서 사용될 경우, 실제 사용자의 질의는 다양한 유형으로 나타나게 된다. 따라서 실용적인 시스템에서 사용되는 질의는 문장의 형태나 단어의 쓰임에 관계없이 같은 의도를 가진 질의를 같은 유형으로 분류할 수 있는 의문형 문장패턴을 태깅하여 다양한 형태의 자연어로 기술된 문서에서 원하는 응답으로 처리할 수 있는 질의 응답 시스템은 정보 검색 시스템으로서의 가능성을 보여준다.

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