• KIPS Transactions on Software and Data Engineering
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• v.1 no.2
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• pp.91-102
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• 2012

Computer aided language learning has become popular. But the level of automation of constructing a Korean learning assistant system is not so high because a practical language learning system needs large scale knowledge resources, which is very hard to acquire. In this paper, we propose a Korean learning assistant system that utilizes easily obtainable knowledge resources like a corpus, web documents and a lexicon. Our system has three modules - problem solving, pronunciation marker and writing assistant. Automatic problem generator uses a corpus and a lexicon to make problems with one correct answer and three distracters, then verifies their suitability by utilizing frequency information from web documents. We analyze pronunciation rules for a pronunciation marker and recommend appropriate words and sentences in real-time by using data extracted from a corpus. In experiment, we evaluate 400 automatically generated problems, which show 89.9% problem suitability and 64.9% example suitability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.6
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• pp.631-636
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• 2019

In recently, various kinds of services utilizing the location information of the user's smart phone have appeared. Based on this trend, we designed a new type of learning assistant system that utilizes geofencing technology, which is a field of location information technology. This system identifies the location of the classroom using the location information of learner's the smart phone and automatically provides the necessary learning contents to the learner's smart phone when the learner enters the classroom set as the virtual fence area while carrying the smart phone respectively. Our system provides learning contents in a form similar to the form of a message or a mobile coupon and learners are used to such mobile service environments very much. So the use of learning contents provided by our system is expected to help improve the learning effect of learners.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.77-84
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• 2014

The purpose of this study is to explore factors affecting the effect of e-learning, and to find out the casual relationship among these factors. Subjects are 2,091 students who have participated in e-learning based class during the period of second semester in 2013. Those of them, 1,732 students response to the survey questions. After gathering data, they are analyzed by using Confirmative Factor Analysis and Structural Equation Modeling. From the result of Confirmative Factor analysis, data have reduced four factors, and are named as four latent variables likes e-learning effect, contents satisfaction, managing assistant factor, and system functional factor. From the result of Structural Equation Modeling, it is known as the relation and impact among factors: (a) "managing assistant factor" affects to "contents satisfaction" directly. (b) "contents satisfaction" affects to "e-learning effect" directly. (c) "system function factor" affects directly to "contents satisfaction", but does not affect directly to "e-learning effect". (d) both "managing assistant factor" and "system function factor" have an indirect effect on "e-learning effect" via "contents satisfaction".

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.41-48
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• 2022

As the COVID-19 situation continues, early childhood are unable to attend early childhood education institutions and are spending more time with their parents at home. Parents are faced with a situation where they have to spend a lot of time at home to teach their children for Korean word learning or play activities. This act as a lot of psychological burden and stress for parents. In order to relieve the psychological burden of parents, the design and implementation of early childhood learning assistant system that can support Korea word education and play activities using artificial intelligence blocks of block coding technique was proposed in this study. The usage of a proposed system can not only reduce the burden on parents for their children's learning, but also can be actively used in the field of early childhood education so many learning effects can be expected.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.273-283
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• 2022

Banking and finance is a broad term that incorporates a variety of smaller, more specialized subjects such as corporate finance, tax finance, and insurance finance. A virtual assistant that assists users in searching for information about banking and finance terms might be an extremely beneficial tool for users. In this study, we explored the process of searching for information, seeking opportunities, and developing a virtual assistant in the first stages of starting learning and understanding Vietnamese to increase effectiveness and save time, which is also an innovative business practice in Use-case Vietnam. We built the FIBA2020 dataset and proposed a pipeline that used Natural Language Processing (NLP) inclusive of Natural Language Understanding (NLU) algorithms to build chatbot applications. The open-source framework RASA is used to implement the system in our study. We aim to improve our model performance by replacing parts of RASA's default tokenizers with Vietnamese tokenizers and experimenting with various language models. The best accuracy we achieved is 86.48% and 70.04% in the ideal condition and worst condition, respectively. Finally, we put our findings into practice by creating an Android virtual assistant application using the model trained using Whitespace tokenizer and the pre-trained language m-BERT.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.826-836
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• 2016

Mastering a musical instrument for an unskilled beginning learner is not an easy task. It requires playing every note correctly and maintaining the tempo accurately. Any music comes in two forms, a music score and it rendition into an audio music. The proposed method of assisting beginning music players in both aspects employs two popular pattern recognition methods for audio-visual analysis; they are support vector machine (SVM) for music score recognition and hidden Markov model (HMM) for audio music performance tracking. With proper synchronization of the two results, the proposed music learning assistant system can give useful feedback to self-training beginners.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.142-150
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• 2006

This study examines whether the reinforcement theory would be effectively applied to teaching assistant robots between a robot and a student in the same way as it is applied to teaching methods between a teacher and a student. Participants interact with a teaching assistant robot in a 3 (types of robots: positive reinforcement vs. negative reinforcement vs. both reinforcements) by 2 (types of participants: honor students vs. backward students), within-subject experiment. Three different types of robots, such as 'Ching-chan-ee' which gives 'positive reinforcement', 'Um-bul-ee' which gives 'negative reinforcement', and 'Sang-bul-ee' which gives both 'positive and negative reinforcement' are designed based on the reinforcement theory and the token reinforcement system. Participants' task performance and reaction rate are measured according to the types of robots and the types of participants. In task performance, the negative reinforcement robot is more effective than the other two types, but regarding the number of stimulus, the less the stimulus is, the more effective the task performance is. Also, participants showed the highest reaction rate on the negative reinforcement robot which implies that the negative reinforcement robot is most effective to motivate students. The findings demonstrate that the participants perceive the teaching assistant robot not as a toy but as a teaching assistant and the reinforcement interaction is important and effective for teaching assistant robots to motivate students. The results of this study can be implicated as an effective guideline to interaction design of teaching assistant robots.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.355-357
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• 2019

Now that we are entering an aging society, the user interface for new devices and IoT technology is very inconvenient for senior generation. To improve this, we propose an AI technology-based intelligent senior assistant voice recognition system. This system implements Cloud platform based API to accumulate data for machine learning processing, provides content for diagnosis and prevention of dementia, and provide chat-bot content for senior generation. We hope that senior generations will increase the accessibility and convenience of IoT devices and new technology devices with our system.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1347-1356
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• 2017

Artificial intelligence-based services are expanding into a new industrial revolution. There is artificial intelligence technology applied in real life due to the development of big data and deep learning related technology. And data analysis and intelligent assistant services that integrate information from various fields have also been commercialized. Chatbot with interactive artificial intelligence provide shopping, news or information. Chatbot service, which has begun to be adopted by some public institutions, is now just a first step in the steps. This study summarizes the services and technical analysis of chatbot. and the direction of public administration service chatbot was presented.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.127-135
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• 2024

Recent studies have shown that inverse design using deep learning has the potential to rapidly generate the optimal design that satisfies the target performance without the need for iterative optimization processes. Unlike traditional methods, deep learning allows the network to rapidly generate a large number of solution candidates for the same objective after a single training, and enables the generation of diverse designs tailored to the objectives of inverse design. These inverse design techniques are expected to significantly enhance the efficiency and innovation of design processes in various fields such as aerospace, biology, medical, and engineering. We analyzes inverse design models that are mainly utilized in the nano and chemical fields, and proposes inverse design models based on supervised and unsupervised learning that can be applied to the engineering system. It is expected to present the possibility of effectively applying inverse design methodologies to the design optimization problem in the field of engineering according to each specific objective.