Towards better transition modeling in recurrent neural networks: The case of sign language tokenization

Pierre Poitier, Jérôme Fink, Benoît Frénay

Abstract: Highlights•Sign language tokenization is a challenging task involving complex transitions.•The limitations of RNNs highlighted in theory can be observed in practice.•Extensions have a positive impact, but there is still room for improvement.•Sign language tokenization task could benefit from these improvements.•There is an interest in a better transition modeling in recurrent neural networks.