Deep neural networks (DNNs) for automatic speech recognition (ASR) require large amounts of labelled data, which can be difficult and expensive to collect. However, recent research has shown that some features learned by DNNs are highly transferable to other tasks and datasets. Here we propose to design a multi-lingual training procedure to leverage large amounts […]
Read More