4 accepted papers
Bidirectional long short-term memory (BLSTM) recurrent neural networks are powerful acoustic models in terms of recognition accuracy. When BLSTM acoustic models are used in decoding, the speech decoder needs to wait until the end of a whole sentence is reached, such that forward-propagation in the b…
Recently, recurrent neural network with bidirectional Long Short-Term Memory (RNN-BLSTM) acoustic model has been shown to give great performance on the TIMIT [1] and other speech recognition tasks. Meanwhile, the speaker code based adaptation method has been demonstrated as a valid adaptation method…
This paper presents a study on large vocabulary continuous whisper automatic recognition (wLVCSR). wLVCSR provides the ability to use ASR equipment in public places without concern for disturbing others or leaking private information. However the task of wLVCSR is much more challenging than normal L…
Recently, we have proposed a general adaptation scheme for deep neural network based on discriminant condition codes and applied it to supervised speaker adaptation in speech recognition based on either frame-level cross-entropy or sequence-level maximum mutual information training criterion [1, 2,…