Improving speech recognition on a mobile robot platform through the use of top-down visual queues
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|Title:||Improving speech recognition on a mobile robot platform through the use of top-down visual queues||Authors:||Ross, Robert
O'Donoghue, R. P. S.
O'Hare, G. M. P. (Greg M. P.)
|Permanent link:||http://hdl.handle.net/10197/4530||Date:||9-Aug-2003||Abstract:||In many real-world environments, Automatic Speech Recognition (ASR) technologies fail to provide adequate performance for applications such as human robot dialog. Despite substantial evidence that speech recognition in humans is performed in a top-down as well as bottom-up manner, ASR systems typically fail to capitalize on this, instead relying on a purely statistical, bottom up methodology. In this paper we advocate the use of a knowledge based approach to improving ASR in domains such as mobile robotics. A simple implementation is presented, which uses the visual recognition of objects in a robot's environment to increase the probability that words and sentences related to these objects will be recognized.||Type of material:||Conference Publication||Publisher:||IJCAI Workshop||Keywords:||Automatic Speech Recognition (ASR);Mobile robotics;Speech priming model||Language:||en||Status of Item:||Peer reviewed||Is part of:||Proceedings of 18th International Joint Conference on Artificial Intelligence (IJCAI-03), 9th-15th August, Acapulco, Mexico||Conference Details:||The 18th International Joint Conference on Artificial Intelligence (IJCAI-03), Acapulco, Mexico, 9-15 August 2003|
|Appears in Collections:||Computer Science Research Collection|
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