@inproceedings {PN16309,
	title = {A Hybrid Framework for Ego Noise Cancellation of a Robot},
	author = {G{\"o}khan Ince AND Kazuhiro Nakadai AND Tobias Rodemann AND Yuji Hasegawa AND Hiroshi Tsujino AND Jun-ichi Imura},
	year = {2010},
	abstract = {Noise generated due to the motion of a robot is not desired, because it deteriorates the quality and intelligibility of the sounds recorded by robot-embedded microphones. It must be reduced or cancelled to achieve automatic speech recognition with a high performance. In this work, we divide ego-motion noise problem into three subdomains of arm, leg and head motion noise, depending on their complexity and intensity levels. We investigate methods that make use of singlechannel and multi-channel processing in order to suppress ego noise separately. For this purpose, a framework consisting of a microphone-array-based geometric source separation, a consequent post filtering process and a parallel module for template subtraction is used. Furthermore, a control mechanism is proposed, which is based on signal-to-noise ratio and instantaneously detected motions, to switch to the most suitable method to deal with the current type of noise. We evaluate the proposed techniques on a humanoid robot using automatic speech recognition (ASR). The preliminary results of isolated word recognition show the effectiveness of our methods by increasing the word correct rates up to 50\% compared to the single channel recognition in arm and leg motion noises and up to 25\% in very strong head motion noises.},
	publisher = {2010 IEEE International Conference on Robotics and Automation},
	address = {Anchorage, Alaska, USA}
}