• Title/Summary/Keyword: Language Convergence

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Dependency parsing applying reinforced dominance-dependency constraint rule: Combination of deep learning and linguistic knowledge (강화된 지배소-의존소 제약규칙을 적용한 의존구문분석 모델 : 심층학습과 언어지식의 결합)

  • JoongMin Shin;Sanghyun Cho;Seunglyul Park;Seongki Choi;Minho Kim;Miyeon Kim;Hyuk-Chul Kwon
    • Annual Conference on Human and Language Technology
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    • 2022.10a
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    • pp.289-294
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    • 2022
  • 의존구문분석은 문장을 의존관계(의존소-지배소)로 분석하는 구문분석 방법론이다. 현재 사전학습모델을 사용한 전이 학습의 딥러닝이 좋은 성능을 보이며 많이 연구되지만, 데이터셋에 의존적이며 그로 인한 자료부족 문제와 과적합의 문제가 발생한다는 단점이 있다. 본 논문에서는 언어학적 지식에 기반한 강화된 지배소-의존소 제약규칙 에지 알고리즘을 심층학습과 결합한 모델을 제안한다. TTAS 표준 가이드라인 기반 모두의 말뭉치로 평가한 결과, 최대 UAS 96.28, LAS 93.19의 성능을 보였으며, 선행연구 대비 UAS 2.21%, LAS 1.84%의 향상된 결과를 보였다. 또한 적은 데이터셋으로 학습했음에도 8배 많은 데이터셋 학습모델 대비 UAS 0.95%의 향상과 11배 빠른 학습 시간을 보였다. 이를 통해 심층학습과 언어지식의 결합이 딥러닝의 문제점을 해결할 수 있음을 확인하였다.

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Qualitative Exploration on Children's Interactions in Telepresence Robot Assisted Language Learning (원격로봇 보조 언어교육의 아동 상호작용 질적 탐색)

  • Shin, Kyoung Wan Cathy;Han, Jeong-Hye
    • Journal of the Korea Convergence Society
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    • v.8 no.3
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    • pp.177-184
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    • 2017
  • The purpose of this study was to explore children and robot interaction in distant language learning environments using three different video-conferencing technologies-two traditional screen-based videoconference technologies and a telepresence robot. One American and six Korean elementary school students participated in our case study. We relied on narratives of one-on-one interviews and observation of nonverbal cues in robot assisted language learning. Our findings suggest that participants responded more positively to interactions via a telepresence robot than to two screen-based video-conferencings, with many citing a stronger sense of immediacy during robot-mediated communications.

Machine Learning Based Domain Classification for Korean Dialog System (기계학습을 이용한 한국어 대화시스템 도메인 분류)

  • Jeong, Young-Seob
    • Journal of Convergence for Information Technology
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    • v.9 no.8
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    • pp.1-8
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    • 2019
  • Dialog system is becoming a new dominant interaction way between human and computer. It allows people to be provided with various services through natural language. The dialog system has a common structure of a pipeline consisting of several modules (e.g., speech recognition, natural language understanding, and dialog management). In this paper, we tackle a task of domain classification for the natural language understanding module by employing machine learning models such as convolutional neural network and random forest. For our dataset of seven service domains, we showed that the random forest model achieved the best performance (F1 score 0.97). As a future work, we will keep finding a better approach for domain classification by investigating other machine learning models.

Fast Convergence GRU Model for Sign Language Recognition

  • Subramanian, Barathi;Olimov, Bekhzod;Kim, Jeonghong
    • Journal of Korea Multimedia Society
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    • v.25 no.9
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    • pp.1257-1265
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    • 2022
  • Recognition of sign language is challenging due to the occlusion of hands, accuracy of hand gestures, and high computational costs. In recent years, deep learning techniques have made significant advances in this field. Although these methods are larger and more complex, they cannot manage long-term sequential data and lack the ability to capture useful information through efficient information processing with faster convergence. In order to overcome these challenges, we propose a word-level sign language recognition (SLR) system that combines a real-time human pose detection library with the minimized version of the gated recurrent unit (GRU) model. Each gate unit is optimized by discarding the depth-weighted reset gate in GRU cells and considering only current input. Furthermore, we use sigmoid rather than hyperbolic tangent activation in standard GRUs due to performance loss associated with the former in deeper networks. Experimental results demonstrate that our pose-based optimized GRU (Pose-OGRU) outperforms the standard GRU model in terms of prediction accuracy, convergency, and information processing capability.

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.

Development of a C-Language Learning Tool using Console Wrapper (Console Wrapper를 활용한 C언어 학습도구 개발)

  • Hwang, Giu-Duck;Choi, Sook-Young
    • Journal of Digital Convergence
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    • v.7 no.3
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    • pp.113-122
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    • 2009
  • The majority of programming education in the learning place attaches importance more to grammar, memorization of the imperative sentence and explanation of the program language itself than the specific way to use the target language. In addition, it is mainly used to teach theoretical knowledge based on the text. Consequently, current programming education has not interested learners in the programming learning and has not improved their ability in programming problems of the real world. We therefore developed a learning tool of C-language, which is based on the Console Wrapper. The purpose of proposing the learning tool was to make the programming education break from the typical theoretical learning and to let learners be interested in the programming education. By using the dynamic screen instead of the static console screen, the learners could enjoy learning the program. As a result of this study, we could know that the programming education using our learning tool is more effective than the typical C language programming education.

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Emotion Analysis of Characters in a Comic from State Diagram via Natural Language-based Requirement Specifications

  • Ye Jin Jin;Ji Hoon Kong;Hyun Seung Son;R. Young Chul Kim
    • International journal of advanced smart convergence
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    • v.13 no.1
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    • pp.92-98
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    • 2024
  • The current software industry has an emerging issue with natural language-based requirement specifications. However, the accuracy of such requirement analysis remains a concern. It is noted that most errors still occur at the requirement specification stage. Defining and analyzing requirements based on natural language has become necessary. To address this issue, the linguistic theories of Chomsky and Fillmore are applied to the analysis of natural language-based requirements. This involves identifying the semantics of morphemes and nouns. Consequently, a mechanism was proposed for extracting object state designs and automatically generating code templates. Building on this mechanism, I suggest generating natural language-based comic images. Utilizing state diagrams, I apply changes to the states of comic characters (protagonists) and extract variations in their expressions. This introduces a novel approach to comic image generation. I anticipate highly productive comic creation by applying software processes to Cartoon ART.

Study on Zero-shot based Quality Estimation (Zero-Shot 기반 기계번역 품질 예측 연구)

  • Eo, Sugyeong;Park, Chanjun;Seo, Jaehyung;Moon, Hyeonseok;Lim, Heuiseok
    • Journal of the Korea Convergence Society
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    • v.12 no.11
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    • pp.35-43
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    • 2021
  • Recently, there has been a growing interest in zero-shot cross-lingual transfer, which leverages cross-lingual language models (CLLMs) to perform downstream tasks that are not trained in a specific language. In this paper, we point out the limitations of the data-centric aspect of quality estimation (QE), and perform zero-shot cross-lingual transfer even in environments where it is difficult to construct QE data. Few studies have dealt with zero-shots in QE, and after fine-tuning the English-German QE dataset, we perform zero-shot transfer leveraging CLLMs. We conduct comparative analysis between various CLLMs. We also perform zero-shot transfer on language pairs with different sized resources and analyze results based on the linguistic characteristics of each language. Experimental results showed the highest performance in multilingual BART and multillingual BERT, and we induced QE to be performed even when QE learning for a specific language pair was not performed at all.

A Study on Foreigners' Korean Language Learning Experiences through Design Thinking Analysis (디자인 사고 분석을 통한 외국인의 한국 언어 학습의 연구)

  • Lee, Pei Zhi;Kim, Boyeun
    • Journal of Digital Convergence
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    • v.15 no.5
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    • pp.345-351
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    • 2017
  • The international status of the Korean language has been elevated as the demand for studying the language among foreign students has grown sharply over the past few years. Unfortunately, foreign students face difficulties in learning the language, conflicts are also deepening between Korean and foreign students. Using Erin Sander's design research spiral, this paper investigates foreigners' Korean language learning experiences, identify the main cognitive and affective factors influencing their learning process. Research findings collected with the design analysis revealed needs and insights that offer opportunities relevant specifically for the conception, design and development of new products and services related to Korean language learning.

A Study on Improving English Pronunciation and Intonation utilizing Fluency Improvement system (음성인식 학습 시스템활용 영어 발음 및 억양 개선방안에 관한 연구)

  • Yi, Jae-Il;Kim, Young-Kwon;Kim, Gui-Jung
    • Journal of the Korea Convergence Society
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    • v.8 no.11
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    • pp.1-6
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    • 2017
  • This paper focuses on the development of a system that improves the convenience of foreign language learning and enhaces the learning ability of the target language through the use of IT devices. In addition to the basic grammar, the importance of pronunciation and intonation have somewhat crucial effect in everyday communication. Pronunciation and intonation of English are different according to the basic characteristics of a native language and these differences often cause problems in communication. The proposed system distinguishes acceptability in English communication process and requests the correction in realtime. The proposed system minimizes system intervention by collecting various voice signals of foreign language learners and setting that can be considered as acceptable threshold points. As a result, the learner can increase the learning efficiency with minimal interruption of the utterance caused by unnecessary system intervention.