Yuya Akita

Data selection from multiple ASR systems' hypotheses for unsupervised acoustic model training

2016

This paper addresses unsupervised training of DNN acoustic model, by exploiting a large amount of unlabeled data with CRF-based classifiers. In the proposed scheme, we obtain ASR hypotheses by complementary GMM and DNN based ASR …