Publication Details
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Yadisbel Martinez Cañete, Hichem Sahli, Abel Díaz Berenguer
 

Springer Lecture Notes in Computer Science. Pattern Recognition and Image Analysis.

Contribution To Book Anthology

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.

Reference 
 
 
DOI scopus springer