TAILIEUCHUNG - Báo cáo khoa học: "A HYBRID REASONING MODEL FOR INDIRECT ANSWERS"

This paper presents our implemented computational model for interpreting and generating indirect answers to Yes-No questions. Its main features are 1) a discourse-plan-based approach to implicature, 2) a reversible architecture for generation and interpretation, 3) a hybrid reasoning model that employs both plan inference and logical inference, and 4) use of stimulus conditions to model a speaker's motivation for providing appropriate, unrequested information. The model handles a wider range of types of indirect answers than previous computational models and has several significant advantages. . | A HYBRID REASONING MODEL FOR INDIRECT ANSWERS Nancy Green Department of Computer Science University of Delaware Newark DE 19716 USA Internet green@ Sandra Carberry Department of Computer Science University of Delaware Visitor Inst for Research in Cognitive Science University of Pennsylvania Internet carberry@ Abstract This paper presents our implemented computational model for interpreting and generating indirect answers to Yes-No questions. Its main features are 1 a discourse-plan-based approach to implicature 2 a reversible architecture for generation and interpretation 3 a hybrid reasoning model that employs both plan inference and logical inference and 4 use of stimulus conditions to model a speaker s motivation for providing appropriate unrequested information. The model handles a wider range of types of indirect answers than previous computational models and has several significant advantages. 1. INTRODUCTION Imagine a discourse context for 1 in which R s use of just Id is intended to convey a No . that R is not going shopping tonight. By convention square brackets indicate that the enclosed text was not explicitly stated. The part of R s response consisting of Id - le is what we call an indirect answer to a Yes-No question and if 1c had been uttered 1c would have been called a direct answer. . Q I need a ride to the mall. b. Are you going shopping tonight c. R no d. My car s not running. e. The rear axle is broken. According to one study of spoken English Stenstrom 1984 13 percent of responses to Yes-No questions were indirect answers. Thus the ability to interpret indirect answers is required for robust dialogue systems. Furthermore there are good reasons for generating indirect answers instead of just yes no or I don t know. First they may provide information which is needed to avoid misleading the questioner Hirschberg 1985 . Second they contribute to an efficient dialogue by anticipating follow-up questions. Third they may be used .

• Báo cáo khoa học
• A HYBRID REASONING MODEL
• INDIRECT ANSWERS
• Nancy Green
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Bài giảng Xử lý ngôn ngữ tự nhiên
• Ngôn ngữ tự nhiên
• Kỹ thuật lập trình
• Xử lý nhập nhằng ngữ nghĩa
• Xử lý ngữ nghĩa
• Xử lý ngôn ngữ
• Natural Language Processing
• Ngôn ngữ lập trình
• Nhập nhằng cấu trúc
• Tri thức về ngôn ngữ
• Mô hình n gram
• Dịch máy
• Phương pháp dịch máy
• Hiểu ngôn ngữ
• Phân tích ngữ nghĩa
• Phân loại tin tự động
• Biểu diễn vị từ
• Thuộc tính về sự kiện
• Thuộc tính về sự kiện
• Mô hình ngôn ngữ Google Book N grams
• Mô hình ngôn ngữ KenLM
• Phương pháp làm mịn
• Tách từ tiếng Việt
• Gán nhãn từ loại
• Phân tích cú pháp
• Nghĩa từ vựng
• Phân giải nhập nhằng từ
• Phân loại văn bản
• Lexical chain
• Phản hồi thông tin
• Bài toán PTCP
• Cấu trúc ngữ pháp
• Phân tích cú pháp xác suất
• CKY kết hợp xác suất
• Văn phạm phi ngữ cảnh xác suất
• Hình thái học