Exploring architectures, data and units for streaming end-to-end speech recognition with RNN-transducer

ASRU, Volume abs/1801.00841, 2017, Pages 193-199.

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Abstract:

We investigate training end-to-end speech recognition models with the recurrent neural network transducer (RNN-T): a streaming, all-neural, sequence-to-sequence architecture which jointly learns acoustic and language model components from transcribed acoustic data. We explore various model architectures and demonstrate how the model can b...More

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