• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.129-136
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• 2010

In this paper, we present an Example-based Dialogue System for English conversation tutoring. It aims to provide intelligent one-to-one English conversation tutoring instead of old fashioned language education with static multimedia materials. This system can understand poor expressions of students and it enables green hands to engage in a dialogue in spite of their poor linguistic ability, which gives students interesting motivation to learn a foreign language. And this system also has educational functionalities to improve the linguistic ability. To achieve these goals, we have developed a statistical natural language understanding module for understanding poor expressions and an example-based dialogue manager with high domain scalability and several effective tutoring methods.

• Korean Journal of Cognitive Science
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• v.16 no.4
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• pp.351-368
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• 2005

The manual construction of the knowledge-base takes much time and effort, and it is hard to adjust intelligence systems to dynamic and flexible environment. Thus mental development in those systems has been investigated in recent years. Autonomous mental development is a new paradigm for developing autonomous machines, which are adaptive and flexible to the environment. Learning conversation, a kind of mental development, is an important aspect of conversational agents. In this paper, we propose a learning conversation method for conversational agents which uses several promising techniques; speech-act templates and genetic programming. Knowledge acquisition of conversational agents is implemented by finite state machines and templates, and dynamic sentence generation is implemented by genetic programming Several illustrations and usability tests how the usefulness of the proposed method.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.3
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• pp.99-104
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• 2012

The purpose of this study is to develop an educational program for improving conversational skills in military counselors and prove its effects. For statistical analysis, t test to find out homogeneity between the experimental and control group and to find out the differences of two groups, and an evaluation before and after the program to verify the therapeutic effects of the program were each proved by SPSS 15.0 for Windows. The followings are the list of the results. First of all, the program was effective in improving military counseling communication skills. Secondly, it was proved to be effective in improving self-effectiveness in counselors. Thirdly, the program was effective in improving interpersonal communication skills. Fourthly, the program revealed its therapeutic effects. Therefore, it is concluded that the program would help greatly in military counseling and living.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.12
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• pp.552-559
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• 2008

Computing technologies are extending the means by which people communicate. Especially, virtual worlds have recently become successful, due to rapidly improving Information Technologies. Chat is a crucial function in current virtual worlds. We need a realistic and efficient communication framework for multi-agents participating in a virtual world. The main contribution of our work is twofold. First, we propose a realistic communication framework which enables 'Complete Talk' and 'Partial Talk' in terms of spatial relationships between avatar agents. Second, our system reconstructs a dialogue graph which maintains all transcripts in the form of directed graphs with temporal(dialogue sequences) and spatial information(physical positions) about communicating agents.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.58-66
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• 2019

Recognition of named entity such as proper nouns in conversation sentences is the most fundamental and important field of study for efficient conversational information prediction. The most important part of a task-oriented dialogue system is to recognize what attributes an object in a conversation has. The named entity recognition model carries out recognition of the named entity through the preprocessing, word embedding, and prediction steps for the dialogue sentence. This study aims at using user - defined dictionary in preprocessing stage and finding optimal parameters at word embedding stage for efficient dialogue information prediction. In order to test the designed object name recognition model, we selected the field of daily chemical products and constructed the named entity recognition model that can be applied in the task-oriented dialogue system in the related domain.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.565-576
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• 2022

The scope and functions of a conversational agent are gradually expanding. In particular, research and technology development is being conducted on a conversational agent that can speak first without user calls. However, still in its early stages, there is a lack of research on how a preceded utterance conversational agent will affect users. Accordingly, this study conducted a 2×3 mixed design using the user's task performance condition and the agent's self-exposure as independent variables and measured Intimacy, Functional Satisfaction, Psychological Reactance, and Workload as dependent variables to identify the effects of preceded utterance conversational agent on user experience.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.11-22
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• 2022

Recently, research and development using various Artificial Intelligence (AI) technologies are being conducted in the field of education. Among the AI in Education (AIEd), conversational agents are not limited by time and space, and can learn more effectively by combining them with various AI technologies such as voice recognition and translation. This paper conducted a trend analysis on platforms that have a large number of users and used conversational agents for English learning among commercialized application. Currently commercialized educational platforms using conversational agent through trend analysis has several limitations and problems. To analyze specific problems and limitations, a comparative experiment was conducted with the latest pre-trained large-capacity dialogue model. Sensibleness and Specificity Average (SSA) human evaluation was conducted to evaluate conversational human-likeness. Based on the experiment, this paper propose the need for trained with large-capacity parameters dialogue models, educational data, and information retrieval functions for effective English conversation learning.

• The Journal of the Acoustical Society of Korea
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• v.40 no.6
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• pp.660-670
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• 2021

As various people use the cafe for various purposes, it is difficult to hear conversations with the accompanying people due to the noise and background music of people around the respondents. In addition, there is a need for improvement related to the noise and sound inside the cafe, such as making it easier to hear the conversations of nearby users. 212 adult men and women participated in the questionnaire on the survey on cafe acoustics and noise conditions. As a result of the survey, about two-thirds of the respondents said that they did not prefer noisy cafes, and that the noise of cafes had a negative effect. The major source of noise in cafes is the sound of people around users, and more than 40 % of the respondents said that they could not hear well the sound of conversations with their accompanying people due to the sounds of those around them, or that they were concerned about their own conversations being transmitted to those around them. As a result of the survey on cafe sound and noise, it was found that improvements were needed to secure the voice privacy of cafe users as well as the voice intelligibility.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.63-72
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• 2010

In the future warfare, the importance of the counter-fire operation is increasing. The counter-fire operation is divided into offensive counter-fire operation and defensive counter-fire operation. Reviewing the researches done so far, the detection asset of offensive counter-fire operation called UAV(Unmanned Aerial Vehicle) and its operational effectiveness analysis is continually progressing. However, the analysis of the detection asset of defensive counterfire called Target Acquisition Radar(TAR) and its quantitative operational effectiveness are not studied yet. Therefore, in this paper, we studied operational effectiveness of TAR using C2 Theory & MANA Simulation model, and showed clear quantitative analysis results by comparing both cases of using TAR and not using TAR.

• Annual Conference on Human and Language Technology
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• 1993.10a
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• pp.249-260
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• 1993

우리 일상 생활에서 매일 이루어지는 대화(conversation)를 살펴보면, 모든 대화는 어떤 '논제(topic)' 중심으로 이루어진다. 이 논문은 이런 논제 중심의 대화를 인지학적인 견해에서 재고해보고자 한다:논제는 우리의 인지구조로부터 어떻게 선택되며, 채택된 논제는 어떻게 상대방에게 전달되는가?