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Training large, deep neural network acoustic models for speech recognition on large datasets takes a long time on a single GPU, motivating research on parallel training algorithms. We present an approach for training a bidirectional LSTM acoustic model on
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Fast Training Of Deep Neural Networks For Speech Recognition
Training large, deep neural network acoustic models for speech recognition on large datasets takes a long time on a single GPU, motivating research on parallel training algorithms. We present an approach for training a bidirectional LSTM acoustic model on