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National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Goal Oriented and Open Domain Dialogue Management
 Vodolán, Miroslav ; Jurčíček, Filip (advisor) ; Psutka, Josef (referee) ; Šedivý, Jan (referee)
Title: Goal Oriented and Open Domain Dialogue Management Author: Miroslav Vodolán Department: Institute of Formal and Applied Linguistics Supervisor: Ing. Mgr. Filip Jurčíček, Ph.D., Institute of Formal and Applied Linguistics Abstract: This thesis proposes novel approaches for dialogue management in dialogue sys- tems. It covers goal-oriented and open domain dialogue systems. In both setups, it helps to improve quality of dialogues between the system and its users: 1) In the case of goal-oriented dialogues, we improve the accuracy of dialogue state tracking methods of spoken dialogue systems. Our approach limits the effect of automatic speech recognition (ASR) errors. We incrementally enhance our interpretable rule-based core by complex neural networks. The resulting system achieves several published state-of-the-art results on public datasets. 2) Effective dialogue management in open domain dialogue is a difficult prob- lem, which highlights the challenges of natural language processing. In this thesis, we propose a principal solution to develop dialogue systems in open domains. The key idea of our approach is building dialogue systems which interactively learn from dialogues with users. The interactive learning enables the system to improve and to extend its knowledge base continually. As a part of this...
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Development Environment Extending the Dialog Management Options of AIML
 Brodec, Václav ; Kuboň, Vladislav (advisor) ; Plátek, Ondřej (referee)
The AIML language was created with a goal of authoring of simple chat bots. Therefore it lacks some of the features of advanced dialog systems. One of them is the support for dialog management, which is beneficial in many applications that the language has already spread into due to its popularity. This thesis solves the problem of dialog management implementation in pure AIML by using the augmented transition networks in design and code generation. It results in a development environment that supports the chosen solution, thus facilitating the design of more complex bots, while maintaining compatibility with standard interprets.
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