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dc.contributor.authorAlexandridis, Aen_NZ
dc.contributor.authorGriffin, Aen_NZ
dc.contributor.authorMouchtaris, Aen_NZ
dc.date.accessioned2019-02-19T02:33:35Z
dc.date.available2019-02-19T02:33:35Z
dc.date.copyright2018-08-29en_NZ
dc.identifier.citationMMSP 2018, IEEE 20th International Workshop on Multimedia Signal Processing, August 29-31 2018, Vancouver, Canada.
dc.identifier.urihttp://hdl.handle.net/10292/12271
dc.description.abstractRecently, wireless acoustic sensor networks (WASNs) have received significant attention from the research community and a variety of methods have been proposed for numerous applications, such as location estimation and speech enhancement. The lack of publicly available datasets with signals recorded in WASNs, presents difficulties in obtaining consistent performance indicators across the different approaches. In this paper, we present and release a dataset of real recorded signals in an outdoor WASN comprised of four microphone arrays. Our dataset consists of several speakers recorded at various locations within the WASN and can be used for benchmarking purposes. We also present location estimation results using our real recorded dataset. Our results can serve as a baseline indicator of localization performance of single and multiple sources in a real environment.
dc.publisherIEEE
dc.relation.urihttp://www.ece.ubc.ca/~mmsp2018/technical/en_NZ
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in (see Citation). The original publication is available at (see Publisher's Version).
dc.titleMultiple Source Location Estimation on a Dataset of Real Recordings in a Wireless Acoustic Sensor Networken_NZ
dc.typeConference Contribution
dc.rights.accessrightsOpenAccessen_NZ
pubs.elements-id343882
aut.relation.conference2018 IEEE 20th International Workshop on Multimedia Signal Processing (MMSP)en_NZ


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