Automatic Classification of Infant Vocalization Sequences with Convolutional Neural Networks

•Small bottlenecks after the convolutional stage primarily raise CNN performance.•Global average pooling layers are most efficient for creating small bottlenecks.•Tuning the convolutional receptive field size is the second most important factor.•Vocalization classes are primarily confused according to their affective similarity.