• Annual Conference on Human and Language Technology
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• 1995.10a
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• pp.310-318
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• 1995

본 논문에서는 한국어의 대표적 일치 현상으로 일컬어지는 존대법을 살펴보고, 영어의 일치 현상과 한국어 존대법 '일치' 현상을 동일한 차원에서 다루는데 대한 문제점을 지적한다. 적어도 최근 생성문법에서 영어나 인구어를 중심으로 도입, 활용되는 Agr과 한국어 존대법은 간과 할 수 없는 중요한 차이점이 있음을 밝힌다. 또한 존대법과 공손법 사이의 연관성을 바탕으로 하여 그 둘을 연결하는 공통의 존대요소를 설정하여 일치현상으로 설명하려 할 경우 모순이 생겨난다는 점과, 이러한 문제는 존대법 자체에도 마찬가지로 적용된다는 점을 지적한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04a
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• pp.523-526
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• 2002

본 논문은 한국어대화에는 주어나 목적어와 같은 구성요소의 빈번한 생략, 존대현상, 존대대명사의 사용 등의 특이한 현상이 나타나는 것을 지적하고, 이러한 한국어대화를 처리하기 위해서는 대화참석자에 관한 정보, 발화문의 화행에 관한 정보, 대화에 관련된 사람들의 사회적 지위에 있어서의 상대적 순위에 관한 정보 등의 상황정보와 정보의 흐름을 이용해야만 한다고 주장한다. 또한, 본 논문은 이러한 상황정보를 전산적으로 어떻게 표기해서 입력하고 한국어대화의 표상구조를 어떠한 형태로 구축하는 것이 타당한지도 자세히 보여 준다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.496-498
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• 2002

한국어 대화에서는 상황에 따라 주어나 목적어가 대화 속의 발화문에서 완전히 생략되기도 하고, 존대현상이 일어나기도 하고, 존대대명사가 사용되기도 한다 본 논문은 이러한 특징적인 언어현상이 일어나는 한국어 대화를 처리하고 그것의 표상구조를 만들기 위해서는 대화참석자에 관한 정보, 발화문의 화형에 관한 정보, 대화에 관련된 사람들의 사회적 지위에 있어서의 상대적 순위에 관한 정보, 대화에 나타나는 발화문 사이의 정보흐름에 관한 정보 등을 명시적으로 표시하고 이용하여야 한다고 주장하며, 또한 이러한 상황정보를 한국어대화표상구조에 구현하는 방법을 제안한다. 본 논문에서 한국어대화표상구조의 구축은 담화표상이론(Discourse Representation Theory)과 분할담화표상이론(Segmented Discourse Representation Theory)을 수정, 확대하여 이루어진다.

• Cross-Cultural Studies
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• v.26
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• pp.509-533
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• 2012

The purpose of this study is to examine the sociolinguistic competence of female marriage-immigrants through analyzing their free colloquial discourse. Because previous studies on female marriage-immigrants have not been performed based on the natural illocutionary data, an accurate diagnosis of their communication method will be necessary for the efficiency of the Korean education aimed at them, and for the development of their communication ability. For this study, the colloquial discourse situation from five female marriage-immigrants from China, the Philippines and Vietnam was recorded. The sociolinguistic characteristics were analyzed centering on the use of designation, respect terms, and regional words. 'Eomma' was used as a designation for their husband's mother, which means that 'intimacy' worked for the designation of their husband's mother. The respect-word classes for others were limited to the 'haeyo' form and the 'hae' one, and the reception for listeners was often discarded. In addition, the influence of regional words was found in the vocabulary and grammar, and the more proficient the Korean language, the more frequent the regional word occurrence. Based on the above result, the teaching method of Korean for the immigrants shall be suggested as follows: the teaching has to focus on respect words positively influencing the relationship with the counterpart.

• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.817-826
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• 2002

In Korean dialogue honorification phenomenon may occur, an honorific pronoun may be used, and a subject or an object may be completely omitted when it can be recovered based on context. This paper proposes that in order to process Korean dialogue in which such distinct linguistic phenomena occur and to construct its representation structure we mark and use the following information explicitly, not implicitly : information about dialogue participants, information about the speech act of an utterance, information about the relative order of social status for the people involved in dialogue, and information flow among utterances of dialogue. In addition, this paper presents a method of marking and using such situational information and an appropriate representation structure of Korean dialogue. In this paper we set up Korean dialogue representation structure by modifying and extending DRT (Discourse Representation Theory) and SDRT (Segmented Discourse Representation Theory). Futhermore, this paper shows how to process Korean dialogue computationally and construct its representation structure by using Prolog programming language, and then applies such representation structure to spontaneous Korean dialogue to know its validity.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.750-761
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• 2021

Even though the replying comments on Internet articles have positive effects on discussions and communications, the malicious comments are still the source of problems even driving people to death. Automatic detection of malicious comments is important in this respect. However, the current filtering method of the malicious comments, based on forbidden words, is not so effective, especially for the replying comments written in Korean. This paper proposes a new filtering approach based on morpheme analysis, identifying coarse and polite morphemes. Based on these two groups of morphemes, the soundness of comments can be calculated. Further, this paper proposes various impact measures for comments, based on the soundness. According to the experiments on malicious comments, one of the impact measures is effective for detecting malicious comments. Comparing our method with the clean-bot of a portal site, the recall is enhanced by 37.93% point and F-measure is also enhanced up to 47.66 points. According to this result, it is highly expected that the new filtering method based on morpheme analysis can be a promising alternative to those based on forbidden words.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.219-240
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• 2023

Conversational AI which allows users to interact with satisfaction is a long-standing research topic. To develop conversational AI, it is necessary to build training data that reflects real conversations between people, but current Korean datasets are not in question-answer format or use honorifics, making it difficult for users to feel closeness. In this paper, we propose a conversation dataset (KOMUChat) consisting of 30,767 question-answer sentence pairs collected from online communities. The question-answer pairs were collected from post titles and first comments of love and relationship counsel boards used by men and women. In addition, we removed abuse records through automatic and manual cleansing to build high quality dataset. To verify the validity of KOMUChat, we compared and analyzed the result of generative language model learning KOMUChat and benchmark dataset. The results showed that our dataset outperformed the benchmark dataset in terms of answer appropriateness, user satisfaction, and fulfillment of conversational AI goals. The dataset is the largest open-source single turn text data presented so far and it has the significance of building a more friendly Korean dataset by reflecting the text styles of the online community.