• Korean Journal of Cognitive Science
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• v.18 no.1
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• pp.1-14
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• 2007

In a goal-oriented dialogue, speakers' intentions can be represented by domain actions that consist of pairs of a speech act and a concept sequence. Therefore, if we plan to implement an intelligent dialogue system, it is very important to correctly infer the domain actions from surface utterances. In this paper, we propose a statistical model to determine speech acts and concept sequences using conditional random fields at the same time. To avoid biased learning problems, the proposed model uses low-level linguistic features such as lexicals and parts-of-speech. Then, it filters out uninformative features using the chi-square statistic. In the experiments in a schedule arrangement domain, the proposed system showed good performances (the precision of 93.0% on speech act classification and the precision of 90.2% on concept sequence classification).

• Korean Journal of Cognitive Science
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• v.18 no.2
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• pp.179-191
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• 2007

In a goal-oriented dialogue, spoken' intentions can be represented by domain actions that consist of pairs of a speech art and a concept sequence. The domain action prediction of user's utterance is useful to correct some errors that occur in a speech recognition process, and the domain action prediction of system's utterance is useful to generate flexible responses. In this paper, we propose a model to predict a domain action of the next utterance using a neural network. The proposed model predicts the next domain action by using a dialogue history vector and a current domain action as inputs of the neural network. In the experiment, the proposed model showed the precision of 80.02% in speech act prediction and the precision of 82.09% in concept sequence prediction.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.561-570
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• 2018

Artificial Intelligence is one of the technologies that are being discussed in the Fourth Industrial Revolution, attracting the attention from companies around the world and this technology is being applied to various industries such as education, finance, automobile, etc. AI integrated ChatBot is a system designed to respond to user questions according to defined response rules. This system is gradually expanded from simple inquiry responses for intelligent virtual assistant service, weather, traffic, schedule, etc. to service provisions through user pattern analysis, to solidify its position as a life-style service. As a result, research on AI integrated ChatBot platform has become necessary. Therefore, this study suggests the design and implementation of an intelligent chatbot service platform for small businesses.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.765-776
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• 2018

Artificial Intelligence is a rapidly growing technology with the latest developments in computing technology and is considered as one of the next major technologies. Chat-Bot is a system that is designed to respond to user's input according to the rules that are set up in advance and it provides more services through simple and repetitive tasks such as counseling, ordering and others. Accordingly, the study aims to present a model of a celeb-bot using Artificial Intelligence. Celeb-Bot is a combination of Celeb, which are short for Celebrity and Chat-bot. Celeb-Bot provides a Chat-Bot service that allows people to talk to a celebrity. The celeb is the best thing to build a relationship and has the advantages of being accessible to anyone. At the same time, Artificial Intelligence is a technology that can be seen as a person, not a product. Based on this, we believe that Celeb's Characteristic and Chat-bot based on artificial intelligence technologies need to be combined, so variety of products can generate synergy. It is predicted that there will be variety of derivatives that utilize this technology, and it is going to present a celeb-bot model accordingly.

• Journal of KIISE:Software and Applications
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• v.35 no.9
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• pp.554-561
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• 2008

Prediction technique of user's intention can be used as a post-processing method for reducing the search space of an automatic speech recognizer. Prediction technique of system's intention can be used as a pre-processing method for generating a flexible sentence. To satisfy these practical needs, we propose a statistical model to predict speakers' intentions that are generalized into pairs of a speech act and a concept sequence. Contrary to the previous model using simple n-gram statistic of speech acts, the proposed model represents a dialogue history of a current utterance to a feature set with various linguistic levels (i.e. n-grams of speech act and a concept sequence pairs, clue words, and state information of a domain frame). Then, the proposed model predicts the intention of the next utterance by using the feature set as inputs of CRFs (Conditional Random Fields). In the experiment in a schedule management domain, The proposed model showed the precision of 76.25% on prediction of user's speech act and the precision of 64.21% on prediction of user's concept sequence. The proposed model also showed the precision of 88.11% on prediction of system's speech act and the Precision of 87.19% on prediction of system's concept sequence. In addition, the proposed model showed 29.32% higher average precision than the previous model.

• Journal of Christian Education in Korea
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• v.75
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• pp.7-31
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• 2023

Purpose of study: The purpose of this essay is to seek an alternative direction for confirmation education within the context of Korean Protestant Church, addressing the following issues: 1) Confusion in the use of terminology on confirmation, 2) Superficial understanding of confirmation, and the absence or privatization of confirmation theology, 3) Formalized confirmation education based on the concept of rites of passage, and 4) The absence of denominationally structured confirmation education. Research content and method: To achieve this purpose, this essay attempts to foster an intradisciplinary and interactive dialogue on confirmation through a biblical, historical, and theological approach. Biblically, confirmation is to be understood as the unity of the baptism of water and the baptism of Holy Spirit, associated with the consecration of the baptized as royal priests through the baptism of Holy Spirit. Historically, as a part of the rite of Christian initiation, confirmation was a unified rite that has undergone a process of separation and reunification. Theologically, the rite of confirmation affirms the covenant of the Triune God given in baptism and is positioned between baptism and the Lord's Supper. Conclusions and Suggestions: In conclusion, this essay suggests an alternative form of Confirmation education that is oriented towards the following objectives: 1) Education that forms the identity given in the baptismal covenant, 2) Education that reflects characteristics of both baptism and the Lord's Supper, 3) Education that integrates the Bible, doctrine, and life of confirmand and, 4) Education based on an organic educational system.