Search Results for author: Arsenii Gorin

Found 4 papers, 1 papers with code

Learning domain-invariant classifiers for infant cry sounds

no code implementations30 Nov 2023 Charles C. Onu, Hemanth K. Sheetha, Arsenii Gorin, Doina Precup

The issue of domain shift remains a problematic phenomenon in most real-world datasets and clinical audio is no exception.

Unsupervised Domain Adaptation

A cry for help: Early detection of brain injury in newborns

no code implementations12 Oct 2023 Charles C. Onu, Samantha Latremouille, Arsenii Gorin, Junhao Wang, Innocent Udeogu, Uchenna Ekwochi, Peter O. Ubuane, Omolara A. Kehinde, Muhammad A. Salisu, Datonye Briggs, Yoshua Bengio, Doina Precup

Since the 1960s, neonatal clinicians have known that newborns suffering from certain neurological conditions exhibit altered crying patterns such as the high-pitched cry in birth asphyxia.

Specificity

Self-supervised learning for infant cry analysis

no code implementations2 May 2023 Arsenii Gorin, Cem Subakan, Sajjad Abdoli, Junhao Wang, Samantha Latremouille, Charles Onu

In this paper, we explore self-supervised learning (SSL) for analyzing a first-of-its-kind database of cry recordings containing clinical indications of more than a thousand newborns.

Domain Adaptation Self-Supervised Learning

CryCeleb: A Speaker Verification Dataset Based on Infant Cry Sounds

2 code implementations1 May 2023 David Budaghyan, Charles C. Onu, Arsenii Gorin, Cem Subakan, Doina Precup

This paper describes the Ubenwa CryCeleb dataset - a labeled collection of infant cries - and the accompanying CryCeleb 2023 task, which is a public speaker verification challenge based on cry sounds.

Speaker Verification

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