@phdthesis {BjoernSchoellingThesis2009,
	title = {Binaural Signal Processing},
	author = {Bj{\"o}rn Sch{\"o}lling},
	year = {2009},
	abstract = {The processing and analysis of audio signals play an important role in the interaction of humans and robots. Crucial for the performance of such methods, e.g. speech recognition and source localization, is that the signal of interest is dominant in comparison to the other perceived audio signals. Interfering speech signals, noise, and echoes (reverbera- tion) lead to a severe degradation in performance, and methods that are able to filter the desired signal have to be implemented. Especially disturbing is noise from the robot itself. Cooling fans of the onboard computer equipment as well as motor noise interfere with the target signal at high power due to their proximity to the microphones. An ad hoc use of state of the art localization and recognition algorithms results in a poor system behavior. The following thesis addresses this issue and presents novel digital signal processing algo- rithms for ego-noise reduction with two microphones. Based on these algorithms, robust source localization and improved speech recognition can be implemented on robotic plat- forms in real environments.},
	address = {Darmstadt},
	institution = {Technische Universit{\"a}t Darmstadt}
}