A Fully Differentiable Beam Search Decoder
Table 1: Comparing WER performance of ASG with decoding grid-search, and DBD, on WSJ. We compare with standard end-to-end approaches, for reference.
['Model', 'nov93dev', 'nov92']
To mitigate overfitting, we trained a variant of our 10M model where the receptive field was reduced to 870ms (leading to 7.5M parameters). While ASG is unable to match the WER performance of the 1450ms receptive field model, training with DBD leads to better performance, demonstrating the advantage of jointly training the acoustic model with the language model. Not only does DBD allow for more compact acoustic models, but also DBD-trained models require much smaller beam at decoding, which brings a clear speed advantage at inference.