Multitask Learning with Low-Level Auxiliary Tasks for Encoder-Decoder Based Speech Recognition
Multitask Learning with Low-Level Auxiliary Tasks for Encoder-Decoder Based Speech Recognition
End-to-end training of deep learning-based models allows for implicit learning of intermediate representations based on the final task loss.However, the end-to-end approach ignores the useful domain knowledge encoded in explicit intermediate-level supervision.We hypothesize that using intermediate representations as auxiliary supervision at lower levels of deep networks may be a good …