A Probabilistic Model for Understanding Composite Spoken Descriptions Makalic, E, Zukerman, I, Niemann, Michael and Schmidt, D 2008, A Probabilistic Model for Understanding Composite Spoken Descriptions, in PRICAI 2008: TRENDS IN ARTIFICIAL INTELLIGENCE, SPRINGER-VERLAG BERLIN,, pp. 750-759. Attached Files Name Description MIMEType Size Downloads Title A Probabilistic Model for Understanding Composite Spoken Descriptions Author(s) Makalic, E Zukerman, I Niemann, Michael orcid.org/0000-0001-6278-7978 Schmidt, D Conference name 10th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2008) Conference location Hanoi, VIETNAM Conference dates 2008/12/15 - 2008/12/19 Title of proceedings PRICAI 2008: TRENDS IN ARTIFICIAL INTELLIGENCE Editor(s) Ho, TB Zhou, ZH Publication date 2008 Series Lecture Notes in Artificial Intelligence Start page 750 End page 759 Total pages 10 Publisher SPRINGER-VERLAG BERLIN Keyword(s) Science & Technology Technology Computer Science, Artificial Intelligence Computer Science ISBN 978-3-540-89196-3 ISSN 0302-9743 Language eng Field of Research 080107 Natural Language Processing 08 Information And Computing Sciences Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture) HERDC Research category EN.1 Other conference paper Persistent URL http://hdl.handle.net/10536/DRO/DU:30095276 Document type: Conference Paper Collection: School of Communication and Creative Arts Related Links Link Description Connect to published version Go to link with your DU access privileges   Connect to Elements publication management system Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Tue, 09 May 2017, 15:10:34 EST Wed, 10 May 2017, 05:03:32 EST Tue, 04 Jul 2017, 16:05:59 EST Thu, 21 Sep 2017, 06:17:50 EST Sat, 14 Oct 2017, 01:30:45 EST Tue, 22 May 2018, 12:26:36 EST Tue, 22 May 2018, 12:28:49 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 4 times in Scopus Search Google Scholar Access Statistics: 5 Abstract Views, 2 File Downloads  -  Detailed Statistics Created: Tue, 04 Jul 2017, 16:05:59 EST

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