담화성분 기반의 한국어 화행 분류를 통한텍스트 의도 파악의 모호성 해소: 전산언어학적 접근
Discourse component-based Korean speech act categorization to resolve the vagueness in understanding text intention: A computational linguistics perspective
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초록
we apply the concept of rhetoricalness and intonation-dependency on the syntax-semantic property ‘discourse component’, to propose a speech act-level categorization for spoken Korean in text form. By this, we primarily aim to make up a non-domain-specific speech act typology that requires less burden in annotation, which also resolves the vagueness in understanding human speech and eventually satisfies the boosting demand for the analysis and understanding of spoken language in speech-based AI services. We constructed the resource for quantitative analysis by annotating 6K Korean utterances, and based on it, via a recurrent neural network-based evaluation, implicitly observed that the proposed speech act typology has consistency in the way it categorizes the utterances. The corpus and trained models are to be distributed online for research purpose
Abstract
we apply the concept of rhetoricalness and intonation-dependency on the syntax-semantic property ‘discourse component’, to propose a speech act-level categorization for spoken Korean in text form. By this, we primarily aim to make up a non-domain-specific speech act typology that requires less burden in annotation, which also resolves the vagueness in understanding human speech and eventually satisfies the boosting demand for the analysis and understanding of spoken language in speech-based AI services. We constructed the resource for quantitative analysis by annotating 6K Korean utterances, and based on it, via a recurrent neural network-based evaluation, implicitly observed that the proposed speech act typology has consistency in the way it categorizes the utterances. The corpus and trained models are to be distributed online for research purpose
참고문헌 (32)
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