Dunstan Baby Language Classification with CNN

Abstract

Several methods were reported in the scientific literature for the classification of the infant cries, in order to automatically detect the need behind their tears and help the parents and caretakers. In the same scope, this paper has an original approach in which the sounds that precede the cry are used. Such sounds can be considered primitive words and are classified according to the “Dunstan Baby Language”. The paper verifies the universal baby language hypothesis starting from the research reported in a previous article. A CNN architecture trained with recordings of babies from Australia was used for classifying the audio material coming from Romanian babies. It was an attempt to see what happens should the participants belong to a different cultural landscape. The database loaded with the sounds made by Romanian babies was labelled by doctors in the maternity hospitals and two Dunstan experts, separately. Finally, the results of the CNN automatic classification were compared to those obtained by the Dunstan coaches. The conclusions have proved that Dunstan language is universal.