title: End-to-End Neural Systems for Automatic Children Speech Recognition: An\n Empirical Study
abstract: A key desiderata for inclusive and accessible speech recognition technology\nis ensuring its robust performance to children's speech. Notably, this includes\nthe rapidly advancing neural network based end-to-end speech recognition\nsystems. Children speech recognition is more challenging due to the larger\nintra-inter speaker variability in terms of acoustic and linguistic\ncharacteristics compared to adult speech. Furthermore, the lack of adequate and\nappropriate children speech resources adds
journal: arXiv (Cornell University)