Information Services banner Edinburgh Research Archive The University of Edinburgh crest

Edinburgh Research Archive >
Informatics, School of >
Informatics Publications >

Please use this identifier to cite or link to this item:

This item has been viewed 4 times in the last year. View Statistics

Files in This Item:

File Description SizeFormat
MooreJ_Automatic Decision Detection.pdf453.11 kBAdobe PDFView/Open
Title: Automatic Decision Detection in Meeting Speech
Authors: Hsueh, Pei-Yun
Moore, Johanna D.
Issue Date: 1-Nov-2010
Journal Title: Proceedings of the 4th international conference on Machine learning for multimodal interaction
Abstract: Decision making is an important aspect of meetings in organisational settings, and archives of meeting recordings constitute a valuable source of information about the decisions made. However, standard utilities such as playback and keyword search are not sufficient for locating decision points from meeting archives. In this paper, we present the AMI DecisionDetector, a system that automatically detects and highlights where the decision-related conversations are. In this paper, we apply the models developed in our previous work [1], which detects decision-related dialogue acts (DAs) from parts of the transcripts that have been manually annotated as extract-worthy, to the task of detecting decision-related DAs and topic segments directly from complete transcripts. Results show that we need to combine features extracted from multiple knowledge sources (e.g., lexical, prosodic, DA-related, and topical class) in order to yield the model with the highest precision. We have provided a quantitative account of the feature class effects. As our ultimate goal is to operate AMI DecisionDetector in a fully automatic fashion, we also investigate the impacts of using automatically generated features, for example, the 5-class DA features obtained in [2].
Keywords: argumentation modelling
meeting tracking and analysis
spoken language understanding
ISBN: 978-3-540-78154-7
ISSN: 0302-9743
Appears in Collections:Informatics Publications

Items in ERA are protected by copyright, with all rights reserved, unless otherwise indicated.


Valid XHTML 1.0! Unless explicitly stated otherwise, all material is copyright © The University of Edinburgh 2013, and/or the original authors. Privacy and Cookies Policy