한국융합학회논문지 (Journal of the Korea Convergence Society)

  • 제12권1호
  • /
  • Pages.57-63
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  • 2021
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  • 2233-4890(pISSN)
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  • 2713-6353(eISSN)
한국융합학회 (Korea Convergence Society)
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발화 의도 예측 및 슬롯 채우기 복합 처리를 위한 한국어 데이터셋 개발

Development of Korean dataset for joint intent classification and slot filling

  • Han, Seunggyu (Department of Computer Science and Engineering, Korea University) ;
  • Lim, Heuiseok (Department of Computer Science and Engineering, Korea University)
  • 투고 : 2020.11.26
  • 심사 : 2021.01.20
  • 발행 : 2021.01.28
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초록

사람의 발화 내용을 이해하도록 하는 언어 인식 시스템은 주로 영어로 연구되어 왔다. 본 논문에서는 시스템과 사용자의 대화 내용을 수집한 말뭉치를 바탕으로 언어 인식 시스템을 훈련시키고 평가할 때 사용할 수 있는 한국어 데이터셋을 개발하고, 관련 통계를 제시한다. 본 데이터셋은 식당 예약이라는 고정된 주제 안에서 사용자의 발화 의도와 슬롯 채우기를 해야 하는 데이터셋이다. 본 데이터셋은 6857개의 한국어 문장으로 이루어져 있으며, 표기된 단어 슬롯의 종류는 총 7개이다. 본 데이터셋에서 표기된 발화의 종류는 총 5개이며, 문장의 발화 내용에 따라 최대 2개까지 동시에 기입되어 있다. 영어권에서 연구된 모델을 본 데이터셋에 적용시켜 본 결과, 발화 의도 추측 정확도는 조금 하락하였고, 슬롯 채우기 F1 점수는 크게 차이나는 모습을 보였다.

Spoken language understanding, which aims to understand utterance as naturally as human would, are mostly focused on English language. In this paper, we construct a Korean language dataset for spoken language understanding, which is based on a conversational corpus between reservation system and its user. The domain of conversation is limited to restaurant reservation. There are 7 types of slot tags and 5 types of intent tags in 6857 sentences. When a model proposed in English-based research is trained with our dataset, intent classification accuracy decreased a little, while slot filling F1 score decreased significantly.

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참고문헌

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