• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• Journal of the Korea Convergence Society
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• v.11 no.1
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• pp.119-130
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• 2020

This study developed an English conversation learning program in immersive virtual reality (VR) environments and compared its effects with non-immersive VR environment using a computer monitor. The effects of the program was assessed using language anxiety and learning achievement. The results indicated that students' language anxiety decreased significantly after learning English conversation in VR environment, but there was no difference between immersive and non-immersive VR. The two VR conditions also produced similar learning outcomes. Future research on immersive VR need to address cyber sickness problems and develop effective learning contents in order to realize its potential for learning.

• 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.