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.
Martinez Cañete, Y, Sahli, H & Diaz Berenguer, A 2023, MULTI-VIEW INFANT CRY CLASSIFICATION. in A Pertusa, AJ Gallego, JA Sánchez & I Domingues (eds), Springer Lecture Notes in Computer Science. Pattern Recognition and Image Analysis.: 11th Iberian Conference on Pattern Recognition and Image Analysis Alicante, Spain, Proceedings. June 27-30, 2023. vol. 14062, Springer, Cham, pp. 639–653, Iberian Conference on Pattern Recognition and Image Analysis, Alicante, Spain, 27/06/23. https://doi.org/10.1007/978-3-031-36616-1_51
Martinez Cañete, Y., Sahli, H., & Diaz Berenguer, A. (2023). MULTI-VIEW INFANT CRY CLASSIFICATION. In A. Pertusa, A. J. Gallego, J. A. Sánchez, & I. Domingues (Eds.), Springer Lecture Notes in Computer Science. Pattern Recognition and Image Analysis.: 11th Iberian Conference on Pattern Recognition and Image Analysis Alicante, Spain, Proceedings. June 27-30, 2023 (Vol. 14062, pp. 639–653). Springer, Cham. https://doi.org/10.1007/978-3-031-36616-1_51
@inbook{07de915d3e2849279a122936ddcacbe6,
title = "MULTI-VIEW INFANT CRY CLASSIFICATION",
abstract = "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.",
keywords = "Classification, Infant cry, Multi-view",
author = "\{Martinez Ca{\~n}ete\}, Yadisbel and Hichem Sahli and \{Diaz Berenguer\}, Abel",
year = "2023",
month = jun,
day = "25",
doi = "10.1007/978-3-031-36616-1\_51",
language = "English",
isbn = "978-3-031-36615-4",
volume = "14062",
pages = " 639–653",
editor = "Antonio Pertusa and Gallego, \{Antonio Javier \} and S{\'a}nchez, \{Joan Andreu\} and In{\^e}s Domingues",
booktitle = "Springer Lecture Notes in Computer Science. Pattern Recognition and Image Analysis.",
publisher = "Springer, Cham",
note = "Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2023 ; Conference date: 27-06-2023 Through 30-06-2023",
url = "http://www.ibpria.org/2023/",
}