11th Annual Conference of the International Speech Communication Association

Makuhari, Chiba, Japan
September 26-30. 2010

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

Gökhan Ince (1), Kazuhiro Nakadai (1), Tobias Rodemann (2), Hiroshi Tsujino (1), Jun-ichi Imura (3)

(1) Honda Research Institute Japan Co. Ltd., Japan
(2) Honda Research Institute Europe GmbH, Germany
(3) Tokyo Institute of Technology, Japan

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.

Full Paper

Bibliographic reference.  Ince, Gökhan / Nakadai, Kazuhiro / Rodemann, Tobias / Tsujino, Hiroshi / Imura, Jun-ichi (2010): "A robust speech recognition system against the ego noise of a robot", In INTERSPEECH-2010, 2070-2073.