• Korean Journal of Cognitive Science
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• v.10 no.2
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• pp.27-34
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• 1999

The main purpose of this paper is to propose a general dialogue flow in 'the a appointment scheduling dialogues' in German using the concept of dialogue acts. A basic a assumption of this research is that dialogue acts contribute to the improvement of a translation system. They might be very useful to solve the problems that syntactic and semantic module could not resolve using contextual knowledge. The classification of the dialogue acts was conducted as a work of VERBMOBIL project and was based on real dialogues transcribed by experts. The real dialogues were analyzed in terms of the dialogue acts. We empirically analyzed the sequences of the dialogue acts not only in a series of dialogue turns but also in one dialogue turn. We attempted to analyZe the sequences in one dialogue turn additionally because the dialogue data used in this research showed some difference from the ones in other existing researches. By examining the sequences in dialogue acts. we proposed the dialogue flowchart in 'the a appointment scheduling dialogues' 'Based on the statistical analysis of the sequences of the most frequent dialogue acts. the dialogue flowcharts seem to represent' the a appointment scheduling dialogues' in general. A further research is required on c classification of dialogue acts which was a base for the analysis of dialogues. In order to e extract the most generalized model. we did not subcategorize each dialogue acts and used a limited number of items of dialogue acts. However. generally defined dialogue acts need to be defined more concretely and new dialogue acts for specific situations should be a added.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.10
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• pp.98-106
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• 1996

This paper proposes an algorithm for analyzing illocutionary force type (IfT)s in a dialogue, based on the context and modal information in the ending of a word. In korean, the variation of an illocutionary force type that represents a speaker's intention frequently occurs at the ending of a word, according to the type of modal information. And in an analysis of speech acts, the modal information illocutionary force types. In this paper, we analyze real dialogue dta, classify the types of illocutionary forces, perform the manual tagging of IFTs and show the freqency of each IFT's occurence. And we also propose an algorithm to extract IFTs, based on the relationship between the analyzed IFTs and the endings of a word. And we use this proposed algorithm to make an experiment on dialogue data and show its efficiency.

• 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).

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.365-368
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• 2005

We propose a speech act analysis method for Korean dialogue using Support Vector Machines (SVM). We use a lexical form of a word, its part of speech (POS) tags, and bigrams of POS tags as sentence features and the contexts of the previous utterance as context features. We select informative features by Chi square statistics. After training SVM with the selected features, SVM classifiers determine the speech act of each utterance. In experiment, we acquired overall $90.54\%$ of accuracy with dialogue corpus for hotel reservation domain.

• The Transactions of the Korea Information Processing Society
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• v.3 no.3
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• pp.417-428
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• 1996

In this paper, a database interface system with natural language dialogue is designed and implemented. The system is made up of language analysis, context processing, dialogue processing and DB processing unit. The method for classifying and processing an undefined word in language analysis is proposed. It reduces the dictionary size, which gives difficulties in DB Interface. And the current DB Interfaces dealt with an input utterance independently. But the system in this paper provides a user with the interface environment in which he or she can have a continuous conversation with the system and retrieve DB information. Thus in this paper, speech acts which include user's inattentions well as propositional contents are defined, and user action hierarchical model for library DB retrieval is constructed. And the system uses the defined knowledge to recognize-user's plan, effectively understanding and managing the ongoing dialogue. And the system is implemented in the domain of library database in order to prove the proposed methods in this paper.

• Journal of KIISE:Software and Applications
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• v.35 no.6
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• pp.374-385
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• 2008

Speech act tagging is an important step in various dialogue applications, which recognizes speaker's intentions expressed in natural language utterances. Previous approaches such as rule-based and statistics-based methods utilize the speech acts of previous utterances and sentence features of the current utterance. This paper proposes a method that determines speech acts of the current utterance using the speech acts of the following utterances as well as previous ones. Using the features of following utterances yields the accuracy 95.27%, improving previous methods by 3.65%. Moreover, sentence features of the previous utterances are employed to maximally utilize the information available to the current utterance. By applying the proper probability model for each speech act, final accuracy of 97.97% is achieved.

• Korean Journal of Cognitive Science
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• v.19 no.3
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• pp.297-310
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• 2008

Since speech acts implies speakers' intentions, it is essential to determine speakers' speech acts if we want to implement an intelligent dialogue system. We propose a two-step model for effectively determining speakers' speech acts. In the first step, the proposed model returns speech act candidates by using a neural network model based on machine learning and a predictivity model based on statistics, respectively. In the second step, using speech act candidates which are returned by the predictivity model, the proposed model filters out speech act candidates which are returned by the neural network model. Then, the proposed model selects a speech act with maximum output value among the unremoved speech act candidates. In the experiment on a schedule management domain, the proposed two-step modeling method showed better precisions than the previous methods only using a machine learning model or a probability model.

• Annual Conference on Human and Language Technology
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• 2017.10a
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• pp.220-224
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• 2017

최근 은행, 보험회사 등 핀테크 관련 업체에서는 챗봇과 같은 인공지능 대화 시스템을 고객상담 업무에 도입하고 있다. 본 논문에서는 금융 도메인을 위한 고객상담 챗봇을 구현하기 위하여, 자연어 이해 기술 중 하나인 고객상담 대화의 도메인 및 화행분류 방법을 제시한다. 이 기술을 통해 자연어로 이루어지는 상담내용을 이해하고 적합한 응답을 해줄 수 있는 기술을 개발할 수 있다. TF-IDF, LDA, 문장 임베딩 등 대화 문장에 대한 자질을 추출하고, 추출된 자질을 Extreme learning machine(ELM)을 통해 도메인 및 화행 분류 모델을 학습한다.

• 한국어정보학회:학술대회논문집
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• 2017.10a
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• pp.220-224
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• 2017

최근 은행, 보험회사 등 핀테크 관련 업체에서는 챗봇과 같은 인공지능 대화 시스템을 고객상담 업무에 도입하고 있다. 본 논문에서는 금융 도메인을 위한 고객상담 챗봇을 구현하기 위하여, 자연어 이해 기술 중 하나인 고객상담 대화의 도메인 및 화행분류 방법을 제시한다. 이 기술을 통해 자연어로 이루어지는 상담내용을 이해하고 적합한 응답을 해줄 수 있는 기술을 개발할 수 있다. TF-IDF, LDA, 문장 임베딩 등 대화 문장에 대한 자질을 추출하고, 추출된 자질을 Extreme learning machine(ELM)을 통해 도메인 및 화행 분류 모델을 학습한다.

• Communications of Mathematical Education
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• v.18 no.2 s.19
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• pp.9-33
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• 2004

The purpose of this paper is to contribute to the dialogue about the notion of advanced mathematical thinking by offering an alternative characterization for this idea, namely advancing mathematical activity. We use the term advancing (versus advanced) because we emphasize the progression and evolution of students' reasoning in relation to their previous activity. We also use the term activity, rather than thinking. This shift in language reflects our characterization of progression in mathematical thinking as acts of participation in a variety of different socially or culturally situated mathematical practices. We emphasize for these practices the changing nature of student' mathematical activity and frame the process of progression in terms of multiple layers of horizontal and vertical mathematizing.