ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global Context
INTERSPEECH, pp. 3610-3614, 2020.
Convolutional neural networks (CNN) have shown promising results for end-to-end speech recognition, albeit still behind other state-of-the-art methods in performance. In this paper, we study how to bridge this gap and go beyond with a novel CNN-RNN-transducer architecture, which we call ContextNet. ContextNet features a fully convolutio...More
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