A Cluster Centroid Method for Room Response Equalization at Multiple Locations (bibtex)
by Sunil Bharitkar, Chris Kyriakakis
Abstract:
In this paper we address the problem of simultaneous room response equalization for multiple listeners. Traditional approaches to this problem have used a single microphone at the listening position to measure impulse responses from a loudspeaker and then use an inverse filter to correct the frequency response. The problem with that approach is that it only works well for that one point and in most cases is not practical even for one listener with a typical ear spacing of 18 cm. It does not work at all for other listeners in the room, or if the listener changes positions even slightly. We propose a new approach that is based on the Fuzzy c-means clustering technique. We use this method to design equalization filters and demonstrate that we can achieve better equalization performance for several locations in the room simultaneously as compared to single point or simple averaging methods.
Reference:
A Cluster Centroid Method for Room Response Equalization at Multiple Locations (Sunil Bharitkar, Chris Kyriakakis), In IEEE Workshop on the Applications of Signal Processing to Audio and Acoustics, 2001.
Bibtex Entry:
@inproceedings{bharitkar_cluster_2001,
	address = {New Platz, NY},
	title = {A {Cluster} {Centroid} {Method} for {Room} {Response} {Equalization} at {Multiple} {Locations}},
	isbn = {0-7803-7126-7},
	url = {http://ict.usc.edu/pubs/A%20CLUSTER%20CENTROID%20METHOD%20FOR%20ROOM%20RESPONSE%20EQUALIZATION%20AT%20MULTIPLE%20LOCATIONS.pdf},
	abstract = {In this paper we address the problem of simultaneous room response equalization for multiple listeners. Traditional approaches to this problem have used a single microphone at the listening position to measure impulse responses from a loudspeaker and then use an inverse filter to correct the frequency response. The problem with that approach is that it only works well for that one point and in most cases is not practical even for one listener with a typical ear spacing of 18 cm. It does not work at all for other listeners in the room, or if the listener changes positions even slightly. We propose a new approach that is based on the Fuzzy c-means clustering technique. We use this method to design equalization filters and demonstrate that we can achieve better equalization performance for several locations in the room simultaneously as compared to single point or simple averaging methods.},
	booktitle = {{IEEE} {Workshop} on the {Applications} of {Signal} {Processing} to {Audio} and {Acoustics}},
	author = {Bharitkar, Sunil and Kyriakakis, Chris},
	year = {2001},
	pages = {55--58}
}
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