TAILIEUCHUNG - Báo cáo khoa học: "Hybrid Approach to User Intention Modeling for Dialog Simulation"

This paper proposes a novel user intention simulation method which is a data-driven approach but able to integrate diverse user discourse knowledge together to simulate various type of users. In Markov logic framework, logistic regression based data-driven user intention modeling is introduced, and human dialog knowledge are designed into two layers such as domain and discourse knowledge, then it is integrated with the data-driven model in generation time. Cooperative, corrective and selfdirecting discourse knowledge are designed and integrated to mimic such type of users. . | Hybrid Approach to User Intention Modeling for Dialog Simulation Sangkeun Jung Cheongjae Lee Kyungduk Kim Gary Geunbae Lee Department of Computer Science and Engineering Pohang University of Science and Technology POSTECH hugman lcj80 getta gblee @ Abstract This paper proposes a novel user intention simulation method which is a data-driven approach but able to integrate diverse user discourse knowledge together to simulate various type of users. In Markov logic framework logistic regression based data-driven user intention modeling is introduced and human dialog knowledge are designed into two layers such as domain and discourse knowledge then it is integrated with the data-driven model in generation time. Cooperative corrective and selfdirecting discourse knowledge are designed and integrated to mimic such type of users. Experiments were carried out to investigate the patterns of simulated users and it turned out that our approach was successful to generate user intention patterns which are not only unseen in the training corpus and but also personalized in the designed direction. 1 Introduction User simulation techniques are widely used for learning optimal dialog strategies in a statistical dialog management framework and for automated evaluation of spoken dialog systems. User simulation can be layered into the user intention level and user surface utterance level. This paper proposes a novel intention level user simulation technique. In recent years a data-driven user intention modeling is widely used since it is domain- and language independent. However the problem of data-driven user intention simulation is the limitation of user patterns. Usually the response patterns from data-driven simulated user tend to be limited to the training data. Therefore it is not easy to simulate unseen user intention patterns which is quite important to evaluate or learn optimal dialog policies. Another problem is poor user type controllability in a data-driven .

• Báo cáo khoa học
• Hybrid Approach to User Intention Modeling
• Dialog Simulation
• Sangkeun Jung
• báo cáo khoa học
• báo cáo 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 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