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Research interests
My background is in cooperative dialogue planning and spoken dialogue systems, which I developed in the Constructive Dialogue Model framework in my thesis in 1994. The research was inspired by Jens Allwood’s model of Ideal Cooperation and Rational Agency, which I developed and extended into the CDM model in the context of a practical dialogue system in the ESPRIT-II project PLUS (Pragmatic Language Understanding System). The main innovation of the research is to use rationality and cooperative principles to construct a shared dialogue model within which to resolve the underlying goal of the dialogue, and to implement certain communicative principles and obligations as filtering constraints on the planning of dialogue contributions.
I'm especially interested in applying machine learning and soft computing methods to design, develop and discover new possibilities for improving and widening dialogue processing. With the aim of building robust and natural user interfaces that take into account various input modalities, the research focuses on adaptive (agent-based) architectures, modelling interaction strategies, error situations, as well as features and requirements of the user. An important research topic is also to explore the new digital technology and its impact in society: to find possibilities it opens for communication, interaction and expression, and to evaluate dialogue systems and to understand the challenges they pose to human-computer interaction.
I have worked on most ares of Natural Language Processing (morphology, syntax, semantics, discourse), and I'm particulary interested in conversational models and dialogue management. My thesis dealt with cooperative communication from both theoretical side (Allwood's Ideal Cooperation) and practical side (building a response planner for the PLUS dialogue systems, ref to EU-project PLUS), and I developed the Constructive Dialogue Model (CDM) approach to dialogue management. The CDM has its view-point in response planning and co-operative communication: dialogue contributions are constructed as reactions to the previous contribution on the basis of local information, and different pragmatic constraints are used to filter out contextually inappropriate responses. I have also worked on modelling dialogue information (topics and speech acts) for a speech recogniser and a spoken dialogue system, and developed a Topic Model in which the relation between topic types and utterance words is measured by mutual information.
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