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September 2010

A Robust Speech Recognition System against the Ego Noise of a Robot

  • G. Ince, K. Nakadai, T. Rodemann, H. Tsujino, J. Imura,
  • in Proceedings of the 11th Annual Conference of the International Speech Communication Association (INTERSPEECH 2010),
  • International Speech Communication Association ( ISCA ),
  • 2010,
  • pp. 2070-2073,
  • Conference paper

Copyright (C) ISCA

This paper presents a speech recognition system for a mobile robot that attains a high recognition performance, even if the robot generates ego-motion noise. We investigate noise suppression and speech enhancement methods that are based on prediction of ego-motion and its noise. The estimation of egomotion is used for superimposing white noise in a selective manner based on the ego-motion type. Moreover, instantaneous prediction of ego-motion noise is the core concept to establish the following techniques: ego-motion noise suppression by template subtraction and missing feature theory based masking of noisy speech features. We evaluate the proposed technique on a robot using speech recognition results. Adaptive superimposition of white noise achieves up to 20% improvement of word correct rates (WCR) and the spectrographic mask attains an additional improvement of up to 10% compared to the single channel recognition. Index Terms: speech enhancement, noise reduction, ASR

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