tailieunhanh - Báo cáo khoa học: "Learning to Compose Effective Strategies from a Library of Dialogue Components"

This paper describes a method for automatically learning effective dialogue strategies, generated from a library of dialogue content, using reinforcement learning from user feedback. This library includes greetings, social dialogue, chit-chat, jokes and relationship building, as well as the more usual clarification and verification components of dialogue. We tested the method through a motivational dialogue system that encourages take-up of exercise and show that it can be used to construct good dialogue strategies with little effort. . | Learning to Compose Effective Strategies from a Library of Dialogue Components Martijn Spitters Marco De Boni Jakub Zavrel Remko Bonnemal t Textkernel BV Nieuwendammerkade 28 a17 1022 AB Amsterdam NL spitters zavrel bonnema @ Unilever Corporate Research Colworth House Sharnbrook Bedford UK MK44 1LQ Abstract This paper describes a method for automatically learning effective dialogue strategies generated from a library of dialogue content using reinforcement learning from user feedback. This library includes greetings social dialogue chit-chat jokes and relationship building as well as the more usual clarification and verification components of dialogue. We tested the method through a motivational dialogue system that encourages take-up of exercise and show that it can be used to construct good dialogue strategies with little effort. 1 Introduction Interactions between humans and machines have become quite common in our daily life. Many services that used to be performed by humans have been automated by natural language dialogue systems including information seeking functions as in timetable or banking applications but also more complex areas such as tutoring health coaching and sales where communication is much richer embedding the provision and gathering of information in . social dialogue. In the latter category of dialogue systems a high level of naturalness of interaction and the occurrence of longer periods of satisfactory engagement with the system are a prerequisite for task completion and user satisfaction. Typically such systems are based on a dialogue strategy that is manually designed by an expert based on knowledge of the system and the domain and on continuous experimentation with test users. 792 In this process the expert has to make many design choices which influence task completion and user satisfaction in a manner which is hard to assess because the effectiveness of a strategy depends on many different .

• Báo cáo khoa học
• Learning to Compose Effective Strategies
• Library of Dialogue Components
• Martijn Spitters
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Bài giảng Xử lý ngôn ngữ tự nhiên
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• Kỹ thuật lập trình
• Xử lý nhập nhằng ngữ nghĩa
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• Xử lý ngôn ngữ
• Natural Language Processing
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• Mô hình ngôn ngữ Google Book N grams
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• Phương pháp làm mịn
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