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Erich Elsen

Researcher at Google

Publications -  62
Citations -  11729

Erich Elsen is an academic researcher from Google. The author has contributed to research in topics: Deep learning & Recurrent neural network. The author has an hindex of 34, co-authored 58 publications receiving 9102 citations. Previous affiliations of Erich Elsen include Baidu & Stanford University.

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Deep Speech: Scaling up end-to-end speech recognition

TL;DR: Deep Speech, a state-of-the-art speech recognition system developed using end-to-end deep learning, outperforms previously published results on the widely studied Switchboard Hub5'00, achieving 16.0% error on the full test set.
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The State of Sparsity in Deep Neural Networks

TL;DR: It is shown that unstructured sparse architectures learned through pruning cannot be trained from scratch to the same test set performance as a model trained with joint sparsification and optimization, and the need for large-scale benchmarks in the field of model compression is highlighted.
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Efficient Neural Audio Synthesis

TL;DR: A single-layer recurrent neural network with a dual softmax layer that matches the quality of the state-of-the-art WaveNet model, the WaveRNN, and a new generation scheme based on subscaling that folds a long sequence into a batch of shorter sequences and allows one to generate multiple samples at once.