White Papers

Improving Speech Recognition on a Mobile Robot Platform Through the Use of Top-Down Visual Queues

Overview 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. This paper advocates 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.

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Publisher
University of Bremen
File Format
PDF
Date Published
Dec 13, 2008
Format
White Papers
Topics
Voice Recognition, Artificial Intelligence, Software Engineering

University of Bremen White Papers

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