@inproceedings {PN19709,
	title = {Robust Ego Noise Suppression of a Robot},
	author = {G{\"o}khan Ince AND Kazuhiro Nakadai AND Tobias Rodemann AND Hiroshi Tsujino AND Jun-ichi Imura},
	year = {2010},
	abstract = {This paper describes an architecture that can enhance a robot with the capability of performing automatic speech recognition even while the robot is moving. The system consists of three blocks: (1) a multi-channel noise reduction block comprising consequent stages of microphone-array-based sound localization, geometric source separa- tion and post filtering, (2) a single-channel template subtraction block and (3) a speech recognition block. In this work, we specifically investi- gate a missing feature theory based automatic speech recognition (MFT- ASR) approach in block (3), that makes use of spectrotemporal elements that are derived from (1) and (2) to measure the reliability of the au- dio features and to generate masks that filter unreliable speech features. We evaluate the proposed technique on a robot using word error rates. Furthermore, we present a detailed analysis of recognition accuracy to determine optimal parameters. Proposed MFT-ASR implementation at- tains significantly higher recognition performance compared to the per- formances of both single and multi-channel noise reduction methods.},
	publisher = {The Twenty Third International Conference on Industrial, Engineering \& Other Applications of Applied Intelligent Systems IEA-AIE 2010},
	note = {Received Best Student Paper award and best paper nomination.},
	address = {Cordoba (Spain)}
}