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Found 3 papers, 1 papers with code
Exploring Architectures, Data and Units For Streaming End-to-End Speech Recognition with RNN-Transducer
The model consists of an `encoder', which is initialized from a connectionist temporal classification-based (CTC) acoustic model, and a `decoder' which is partially initialized from a recurrent neural network language model trained on text data alone.
Fast and Accurate Recurrent Neural Network Acoustic Models for Speech Recognition
We have recently shown that deep Long Short-Term Memory (LSTM) recurrent neural networks (RNNs) outperform feed forward deep neural networks (DNNs) as acoustic models for speech recognition.
Long Short-Term Memory Based Recurrent Neural Network Architectures for Large Vocabulary Speech Recognition
However, in contrast to the deep neural networks, the use of RNNs in speech recognition has been limited to phone recognition in small scale tasks.
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