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Multi-view Infant Cry Classification

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Pattern Recognition and Image Analysis (IbPRIA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14062))

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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.

Thanks to VLIRUOS for financial support in the framework of the Institutional University Cooperation project with Universidad de Oriente, Cuba.

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Notes

  1. 1.

    https://github.com/gveres/donateacry-corpus.

  2. 2.

    https://github.com/SuperKogito/spafe.

  3. 3.

    https://librosa.org/.

  4. 4.

    https://github.com/kitzeslab/opensoundscape.

  5. 5.

    https://pypi.org/project/disvoice-prosody/.

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Author information

Authors and Affiliations

  1. Universidad de Oriente, Las Americas Ave, 90900, Santiago de Cuba, Cuba

    Yadisbel Martinez-Cañete

  2. Department of Electronics and Informatics, Vrije Universiteit Brussel, Pleinlaan 2, 1050, Brussels, Belgium

    Hichem Sahli & Abel Díaz Berenguer

  3. Interuniversity Microelectronics Centre, Kapeldreef 75, 3001, Heverlee, Belgium

    Hichem Sahli

Authors
  1. Yadisbel Martinez-Cañete
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  2. Hichem Sahli
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  3. Abel Díaz Berenguer
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Corresponding authors

Correspondence to Yadisbel Martinez-Cañete , Hichem Sahli or Abel Díaz Berenguer .

Editor information

Editors and Affiliations

  1. University of Alicante, Alicante, Spain

    Antonio Pertusa

  2. University of Alicante, Alicante, Spain

    Antonio Javier Gallego

  3. Universitat Politècnica de València, Valencia, Spain

    Joan Andreu Sánchez

  4. IPO Porto, Coimbra, Portugal

    Inês Domingues

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Martinez-Cañete, Y., Sahli, H., Berenguer, A.D. (2023). Multi-view Infant Cry Classification. In: Pertusa, A., Gallego, A.J., Sánchez, J.A., Domingues, I. (eds) Pattern Recognition and Image Analysis. IbPRIA 2023. Lecture Notes in Computer Science, vol 14062. Springer, Cham. https://doi.org/10.1007/978-3-031-36616-1_51

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  • DOI: https://doi.org/10.1007/978-3-031-36616-1_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-36615-4

  • Online ISBN: 978-3-031-36616-1

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