A Robust Speech Recognition System for Service-Robotics Applications

  • Masrur Doostdar
  • Stefan Schiffer
  • Gerhard Lakemeyer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5399)

Abstract

Mobile service robots in human environments need to have versatile abilities to perceive and to interact with their environment. Spoken language is a natural way to interact with a robot, in general, and to instruct it, in particular. However, most existing speech recognition systems often suffer from high environmental noise present in the target domain and they require in-depth knowledge of the underlying theory in case of necessary adaptation to reach the desired accuracy. We propose and evaluate an architecture for a robust speaker independent speech recognition system using off-the-shelf technology and simple additional methods. We first use close speech detection to segment closed utterances which alleviates the recognition process. By further utilizing a combination of an FSG based and an N-gram based speech decoder we reduce false positive recognitions while achieving high accuracy.

Keywords

Linear Discriminant Analysis Speech Recognition Language Model False Recognition Speech Recognition System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Masrur Doostdar
    • 1
  • Stefan Schiffer
    • 1
  • Gerhard Lakemeyer
    • 1
  1. 1.Knowledge-based Systems Group Department of Computer Science 5RWTH Aachen UniversityGermany

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