A Bayesian active-learning approach for obtaining notched-noise data

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A Bayesian active-learning approach for obtaining notched-noise data

Schlittenlacher, J; Baer, T; Turner, RE; Moore, BCJ; (2018) A Bayesian active-learning approach for obtaining notched-noise data. In: Seeber, Bernhard, (ed.) Tagungsband: Fortschritte der Akustik – DAGA 2018. (pp. pp. 377-378). Deutsche Gesellschaft für Akustik (DEGA e.V.): Berlin, Germany. Green open access

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Type:	Proceedings paper
Title:	A Bayesian active-learning approach for obtaining notched-noise data
Event:	44. Jahrestagung für Akustik
Location:	Munich
ISBN-13:	978-3-939296-13-3
Open access status:	An open access version is available from UCL Discovery
Publisher version:	https://pub.dega-akustik.de/DAGA_2018/data/welcome...
Language:	English
Additional information:	This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification:	UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Speech, Hearing and Phonetic Sciences
URI:	https://discovery-pp.ucl.ac.uk/id/eprint/10181598

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