Stimulated Deep Neural Network for Speech Recognition

By Chunyang Wu, Panagiota Karanasou, Mark John Francis Gales, Khe Chai Sim. 2016

39 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Dong Yu
2. Li Deng
3. Jinyu Li
4. Jasha Droppo
5. M. Seltzer
6. Mark John Francis Gales
7. Andreas Stolcke
8. Frank Torsten Bernd Seide

In Signal Processing

1. Dong Yu
2. Li Deng
3. Jinyu Li
4. Jasha Droppo
5. M. Seltzer
6. Frank Torsten Bernd Seide
7. Andreas Stolcke
8. Mark John Francis Gales

Citations in the corpus

• Achieving Human Parity in Conversational Speech Recognition (2016, methodology): “Our spatial regularization technique is similar in spirit to stimulated deep neural networks [69].”
• Low-Resource Speech Recognition and Keyword-Spotting (2017, methodology): “To address this problem stimulated network training has been proposed [29,32,25].”
• Toward Human Parity in Conversational Speech Recognition (2017, methodology): “Stimulated networks [58] employ a similar approach.”