A Fully Differentiable Beam Search Decoder
Table 2: WSJ performance (WER), using only the acoustic training data. ASG n-gram decoding hyper-parameters were tuned via grid-search. Beam size for both ASG and DBD was 500. Larger beam sizes with ASG did not lead to significant improvements.
['Model', 'nov93dev', 'nov92']
bilinear language models (where all the parameters are trained jointly with the acoustic model). Results show that only knowing the lexicon when training the acoustic model already greatly improves the WER over the baseline ASG model, where the lexicon is known only at test time. Jointly training a word language model with the acoustic model further reduces the WER.