MULTI-VIEW INFANT CRY CLASSIFICATION

Yadisbel Martinez Cañete, Hichem Sahli, Abel Diaz Berenguer

Onderzoeksoutput: Chapterpeer review

Samenvatting

This paper addresses infant cry classification in multi-view settings, that is, settings where the typical low-level representations, commonly used for audio recognition tasks, are considered as different views of the target data. We show that
through the use of multi-view methods, such as Structured Latent Multi-View Representation Learning, we are able to reliably discriminate between normal and pathological infant cry signals. Extensive experimental results on two benchmark
infant cry data sets indicate that the proposed method outperforms state-of-the-art models.
Originele taal-2English
TitelSpringer Lecture Notes in Computer Science. Pattern Recognition and Image Analysis.
Subtitel11th Iberian Conference on Pattern Recognition and Image Analysis Alicante, Spain, Proceedings. June 27-30, 2023
RedacteurenAntonio Pertusa, Antonio Javier Gallego, Joan Andreu Sánchez, Inês Domingues
UitgeverijSpringer, Cham
Pagina's 639–653
Aantal pagina's15
Volume14062
ISBN van elektronische versie978-3-031-36616-1
ISBN van geprinte versie978-3-031-36615-4
DOI's
StatusPublished - 25 jun 2023
EvenementIberian Conference on Pattern Recognition and Image Analysis - Alicante, Spain
Duur: 27 jun 202330 jun 2023
Congresnummer: 11th
http://www.ibpria.org/2023/

Conference

ConferenceIberian Conference on Pattern Recognition and Image Analysis
Verkorte titelIbPRIA 2023
Land/RegioSpain
StadAlicante
Periode27/06/2330/06/23
Internet adres

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