P
Patrick Nguyen
Researcher at Google
Publications - 137
Citations - 19593
Patrick Nguyen is an academic researcher from Google. The author has contributed to research in topics: Language model & Speaker recognition. The author has an hindex of 44, co-authored 137 publications receiving 17225 citations. Previous affiliations of Patrick Nguyen include Panasonic & Institut Eurécom.
Papers
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Journal ArticleDOI
Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
Geoffrey E. Hinton,Li Deng,Dong Yu,George E. Dahl,Abdelrahman Mohamed,Navdeep Jaitly,Andrew W. Senior,Vincent Vanhoucke,Patrick Nguyen,Tara N. Sainath,Brian Kingsbury +10 more
TL;DR: This article provides an overview of progress and represents the shared views of four research groups that have had recent successes in using DNNs for acoustic modeling in speech recognition.
Journal Article
Deep Neural Networks for Acoustic Modeling in Speech Recognition
Geoffrey E. Hinton,Li Deng,Dong Yu,George E. Dahl,Abdelrahman Mohamed,Navdeep Jaitly,Andrew W. Senior,Vincent Vanhoucke,Patrick Nguyen,Tara N. Sainath,Brian Kingsbury +10 more
TL;DR: This paper provides an overview of this progress and repres nts the shared views of four research groups who have had recent successes in using deep neural networks for a coustic modeling in speech recognition.
Proceedings ArticleDOI
State-of-the-Art Speech Recognition with Sequence-to-Sequence Models
Chung-Cheng Chiu,Tara N. Sainath,Yonghui Wu,Rohit Prabhavalkar,Patrick Nguyen,Zhifeng Chen,Anjuli Kannan,Ron Weiss,Kanishka Rao,Ekaterina Gonina,Navdeep Jaitly,Bo Li,Jan Chorowski,Michiel Bacchiani +13 more
TL;DR: In this article, the authors explore a variety of structural and optimization improvements to the Listen, Attend, and Spell (LAS) encoder-decoder architecture, which significantly improves performance.
Journal ArticleDOI
Rapid speaker adaptation in eigenvoice space
TL;DR: A new model-based speaker adaptation algorithm called the eigenvoice approach, which constrains the adapted model to be a linear combination of a small number of basis vectors obtained offline from a set of reference speakers, and thus greatly reduces the number of free parameters to be estimated from adaptation data.
Proceedings ArticleDOI
On rectified linear units for speech processing
Matthew D. Zeiler,Marc'Aurelio Ranzato,Rajat Monga,Mark Z. Mao,Ke Yang,Quoc V. Le,Patrick Nguyen,Andrew W. Senior,Vincent Vanhoucke,Jeffrey Dean,Geoffrey E. Hinton +10 more
TL;DR: This work shows that it can improve generalization and make training of deep networks faster and simpler by substituting the logistic units with rectified linear units.