• Proceedings of the KSPS conference
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• 2006.11a
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• pp.14-18
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• 2006

The role of dialogue manager is to select proper actions based on observed environment and inferred user intention. This paper presents stochastic model for dialogue manager based on Markov decision process. To build a mixed initiative dialogue manager, we used accumulated user utterance, previous act of dialogue manager, and domain dependent knowledge as the input to the MDP. We also used dialogue corpus to train the automatically optimized policy of MDP with reinforcement learning algorithm. The states which have unique and intuitive actions were removed from the design of MDP by using the domain knowledge. The design of dialogue manager included the usage of natural language understanding and response generator to build short message based remote control of home networked appliances.

• Proceedings of the KSPS conference
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• 2006.11a
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• pp.109-112
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• 2006

This paper presents a dialogue interface using the dialogue management system as a method for controlling home appliances in Home Network Services. In order to realize this type of dialogue interface, we first investigated the user requirements for Home Network Services by analyzing the dialogues entered by users. Based on the analysis, we were able to extract 15 user intentions and 22 semantic components. In our study, example dialogues were collected from WOZ (Wizard-of-OZ) environment to implement a reasoning model for generating meaningful responses for example-based dialogue modeling technique. An overview of the Home Network Control System using proposed dialogue interface will be presented. Lastly, we will show that the Dialogue Management System trained with our collected dialogues behaves properly to achieve its task of controlling Home Network appliances by going through the steps of natural language understanding, response reasoning, response generation.

• Journal of KIISE:Software and Applications
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• v.34 no.2
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• pp.123-130
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• 2007

In this paper, we present an example-based natural language dialogue system for Electronic Program Guide Information Access. We introduce an effective and practical dialogue management technique incorporating dialogue examples and situation-based rules. In order to generate cooperative responses to smoothly lead the dialogue with users, our natural language dialogue system consists of natural language understanding, dialogue manager, system utterance generator. and EPG database manager. Each module is designed and implemented to make an effective and practical natural language dialogue system. In particular, in order to reflect the up-to-date EPG information which is updated frequently and periodically, we applied a web-mining technology to the EPG database manager, which builds the content database based on automatically extracted information from popular EPG websites. The automatically generated content database is used by other modules in the system for building their own resources. Evaluations show that our system performs EPG access task in high performance and can be managed with low cost.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.5
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• pp.55-65
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• 1997

In many cases, a dialogue system can't extract the correct analysis information of a user's spoken utterance, because of its own ungrammatical components. Therefore, in order to perform a correct before it performs the syntactic processing. In this paper, we use a real dialogue corpus and classify these ungrammatical errors as 4 categories : phonological, syntactic, semantic errors that consist of speech reparis and inversions, and propose an algorithm to detect and correct the errors. In short, this paper proposes a method to detect and correct the speech repairs and inversions that are classified as the phonological and syntactic errors to implement a robust dialogue system. And, through the test of real dialogue data, this paper shows an efficiency of the proposed algorithm.

• Journal of Mechanical Science and Technology
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• v.20 no.11
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• pp.1863-1872
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• 2006

In FMS (Flexible Manufacturing System) and CIM (Computer Integrated Manufacturing), machine-tools have been the target of integration in the last three decades. The conventional concept of integration is being changed into the autonomous manufacturing device based on the knowledge evolution by applying advanced information technology in which an open architecture controller, high-speed network and internet technology are included. In the advanced environment, the machine-tools is not the target of integration anymore, but has been the key subject of cooperation. In the near future, machine-tools will be more improved in the form of a knowledge-evolutionary intelligent device. The final goal of this study is to develop an intelligent machine having knowledge-evolution capability and a management system based on internet operability. The knowledge-evolutionary intelligent machine-tools is expected to gather knowledge autonomically, by producing knowledge, understanding knowledge, reasoning knowledge, making a new decision, dialoguing with other machines, etc. The concept of the knowledge-evolutionary intelligent machine is originated from the machine control being operated by human experts' sense, dialogue and decision. The structure of knowledge evolution in M2M (Machine to Machine) and the scheme for a dialogue agent among agent-based modules such as a sensory agent, a dialogue agent and an expert system (decision support agent) are presented in this paper, with intent to develop the knowledge-evolutionary machine-tools. The dialogue agent functions as an interface for inter-machine cooperation. To design the dialogue agent module in an M2M environment, FIPA (Foundation of Intelligent Physical Agent) standard platform and the ping agent based on FIPA are analyzed in this study. In addition, the dialogue agent is designed and applied to recommend cutting conditions and thermal error compensation in a tapping machine. The knowledge-evolutionary machine-tools are expected easily implemented on the basis of this study and shows a good assistance to sensory and decision support agents.

• Journal of Radiation Protection and Research
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• v.48 no.3
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• pp.107-116
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• 2023

This article reviews the experience of applying the Identification, Diagnosis, Prospective, and Action (IDPA) facilitating method as a means of promoting practices of dialogue between stakeholders in the radiological protection field. After presenting the characteristics of the IDPA method and its ability to promote active listening, participation, and dialogue among stakeholders facing complex situations, as well as the procedural aspects associated with its practical implementation, the article describes three examples of the application of the method in the field of radiological protection. The first one presents how the IDPA method supported a debate among decision-makers, authorities, experts, professionals, and representatives of non-governmental organizations about how to engage stakeholders in radiological protection. The second example presents how the IDPA method was used in a series of dialogue meetings to explore the challenges of the post-nuclear accident situation resulting from the Fukushima Daiichi Nuclear Power Plant accident. The third one presents the application of the method in the context of a training course organized by Nagasaki University in the affected area close to the damaged plant. Experience has shown that the IDPA method makes it possible to develop responses to problems posed in very different contexts and, in many cases, to find compromises regarding their solutions. The IDPA method has the merit of allowing each of the participants to better understand the situation they are faced with, even if such a positive result is not always achieved.

• Journal of Sensor Science and Technology
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• v.30 no.6
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• pp.429-435
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• 2021

In this study, the creation of emotional dialogue was investigated within the process of developing a robot's natural language understanding and emotional dialogue processing. Unlike an English-based dataset, which is the mainstay of natural language processing, the Korean-based dataset has several shortcomings. Therefore, in a situation where the Korean language base is insufficient, the Korean dataset should be dealt with in detail, and in particular, the unique characteristics of the language should be considered. Hence, the first step is to base this study on a specific Korean dataset consisting of conversations on emotional topics. Subsequently, a model was built that learns to extract the continuous dialogue features from a pre-trained language model to generate sentences while maintaining the context of the dialogue. To validate the model, a chatbot system was implemented and meaningful results were obtained by collecting the external subjects and conducting experiments. As a result, the proposed model was influenced by the dataset in which the conversation topic was consultation, to facilitate free and emotional communication with users as if they were consulting with a chatbot. The results were analyzed to identify and explain the advantages and disadvantages of the current model. Finally, as a necessary element to reach the aforementioned ultimate research goal, a discussion is presented on the areas for future studies.

• Journal of The Korean Association of Information Education
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• v.24 no.6
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• pp.623-631
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• 2020

In the era of COVID-19 global pandemic, e-learning has become new standards and daily life in the name of 'new normal'. This study developed dialogue e-learning contents as opposed to monologue e-learning which is unidirectional and instructor centered and conducted qualitative user experience evaluation of dialogue e-learning contents. A total number of 20 adult students participated and were individually interviewed. Qualitative data analysis was performed. The findings include students' positive perceptions of dialogue e-learning contents such as empathy for various ideas and new format. With regard to personal preference, 55% of participants preferred dialogue e-learning contents because it enables them to focus and share real experiences. Meanwhile, in terms of learning effects, 60% participants selected monologue e-learning contents and mentioned adequate explanations of concepts and explicit information delivery. Based on the results, suggestions on the design and development of dialogue e-learning contents were presented.

• Korean Journal of Child Studies
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• v.29 no.4
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• pp.181-197
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• 2008

A mobile phone usage survey was administered to a nationwide sample of 3,617 adolescents. Major motivations of mobile phone usage were mobility/real-time connection, show off, information acquisition, entertainment, dialogue, schedule management, and advice. Maintenance of social relationship with the peer group was most important in mobile phone use. Motivations influenced mobile phone dependency : show off had the strongest influence on anxiety/paranoia followed by dialogue, entertainment, mobility/real-time connection. Without their phones, fashion-oriented adolescents showed mobile phone dependency and anxiety. Stronger dialogue and entertainment motivations were associated with weaker real time connection motivation and stronger paranoia symptoms. Mobile phone dependent adolescents had lower grades, showed lack of attention, had little dialogue with their parents and showed withdrawal from the peer group.

• Journal of Korean Academy of Nursing
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• v.39 no.2
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• pp.166-176
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• 2009

Purpose: The purpose of the study was to identify functional structure and patterns of dialogue sequence in conversations between elderly patients with dementia and nurses in a long-term care facility. Methods: Conversation analysis was used to analyze the data which were collected using video-camera to capture non-verbal as well as verbal behaviors. Data collection was done during February 2005. Results: Introduction, assessment, intervention, and closing phases were identified as functional structure. Essential parts of the conversation were the assessment and intervention phases. In the assessment phase three sequential patterns of nurse-initiated dialogue and four sequential patterns of patient-initiated dialogue were identified. Also four sequential patterns were identified in nurse-initiated and three in patient-initiated dialogues in the intervention phase. In general, "ask question", "advise", and "directive" were the most frequently used utterance by nurses in nurse-initiated dialogue, indicating nurses' domination of the conversation. At the same time, "ask back", "refute", "escape", or "false promise" were used often by nurses to discourage patients from talking when patients were raising questions or demanding. Conclusion: It is important for nurses to encourage patient-initiated dialogue to counterbalance nurse-dominated conversation which results from imbalance between nurses and patients in terms of knowledge and task in healthcare institutions for elders.