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On adressee prediction for remote hybrid meeting settings or how to use multiple modalities in predicting whether or not you are being addressed in a live hybrid meeting environment

Akker, H. op den (2009) On adressee prediction for remote hybrid meeting settings or how to use multiple modalities in predicting whether or not you are being addressed in a live hybrid meeting environment.

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Abstract:To answer the question Who said what to whom? is a key part in understanding what is going on in group conversations. The question consists of three parts: who is the source of the message, what does the message entail, and to whom is the message addressed? This master thesis is about the third part of the question: to whom is the message addressed. More specifically, this work tries to create a method for automatically detecting whether a specific member in a group discussion is the intended addressee of an utterance or not. The general approach in this work is the use and creation of machine classifiers. In our case, the machine classifier functions as a piece of software that is working as an assistant for a specific participant in a meeting. The software can help in telling when the participant that it is operating for is being addressed. The details of this will become clear later on. For now, we look at what addressing is and how many different techniques we, humans, deploy in making sure our message reaches the intended audience. The first chapter continues by looking at why we would want to predict this behaviour automatically, and how other researchers in the field have done so.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Human Media Interaction MSc (60030)
Link to this item:http://purl.utwente.nl/essays/58664
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