Adaptation and dialogue modelling for speech-based interaction systems
This event took place on Tuesday 10 May 2005 at 10:00
Prof. Kristiina Jokinen Professor of Language Technology, University of Helsinki
The state-of-the-art speech and language technology has reached a level that allows us to build applications which enable users to have short conversations with the system in search for information like bus or train timetables, telephone numbers, etc. However, interactions are usually characterised by simple predefined interaction patterns which often leave the user frustrated due to their repetitive and unhelpful nature.
In this talk, I will discuss possibilities for making interaction more flexible, intelligent and natural by taking some human language capabilities into account. Especially, I will focus on Constructive Dialogue Management so as to model aspects of interaction that contribute to smoothness of interaction, and on adaptive user modelling so as to take the user's expertise level into account.
Download PowerPoint Presentation (929kb ZIP file)
This event took place on Tuesday 10 May 2005 at 10:00
The state-of-the-art speech and language technology has reached a level that allows us to build applications which enable users to have short conversations with the system in search for information like bus or train timetables, telephone numbers, etc. However, interactions are usually characterised by simple predefined interaction patterns which often leave the user frustrated due to their repetitive and unhelpful nature.
In this talk, I will discuss possibilities for making interaction more flexible, intelligent and natural by taking some human language capabilities into account. Especially, I will focus on Constructive Dialogue Management so as to model aspects of interaction that contribute to smoothness of interaction, and on adaptive user modelling so as to take the user's expertise level into account.
Download PowerPoint Presentation (929kb ZIP file)
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We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.
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