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Comparing models for discrimination of infant cries for the early detection of developmental disorders

Crying is, for babies, the earliest way of expressing and communicating needs like hunger, pain, discomfort or tiredness. Apart from that, the cry is an acoustic signal containing information that provides insights into the medical status of an infant. Much research has been conducted to explore the acoustic properties of infant cries and the potential to identify differences in those properties between healthy and non-healthy cries, using computational models and algorithms as well as by human listeners. Although the previous researches did not examine sufficiently to see if human listeners are able to differentiate not only between healthy and non-healthy cries but also between different types of pathologies and a comparison of the classification skills of computational models in contrast to the skills of human listeners.

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