Mike Schuster

发表

Efficient generation of high-order context dependent weighted finite state transducers for speech recognition

Takaaki Hori, Mike Schuster, 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

Nozomi - a fast, memory-efficient stack decoder for LVCSR

Mike Schuster, 1998, ICSLP.

Better Generative Models for Sequential Data Problems: Bidirectional Recurrent Mixture Density Networks

Mike Schuster, M. Schuster, 1999, NIPS.

Phoneme boundary estimation using bidirectional recurrent neural networks and its applications

Yoshinori Sagisaka, Mike Schuster, Toshiaki Fukada, 1999 .

Experiments with probabilistic principal component analysis in LVCSR

Atsushi Nakamura, Takaaki Hori, Mike Schuster, 2005, INTERSPEECH.

Bidirectional recurrent neural networks

Kuldip K. Paliwal, Mike Schuster, K. Paliwal, 1997, IEEE Trans. Signal Process..

Dynamic planar map illustration

Mike Schuster, Paul Asente, Teri Pettit, 2007, ACM Trans. Graph..

Initial evaluation of hidden dynamic models on conversational speech

Li Deng, Joseph Picone, Terri Kamm, 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

Acoustic model building based on non-uniform segments and bidirectional recurrent neural networks

Mike Schuster, 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation

Martin Wattenberg, Quoc V. Le, Yonghui Wu, 2016, TACL.

Segment boundary estimation using recurrent neural networks

Yoshinori Sagisaka, Mike Schuster, Sophie Aveline, 1997, EUROSPEECH.

Neural Nets for Speech Processing

Mike Schuster, 1999 .

Japanese and Korean voice search

Mike Schuster, Kaisuke Nakajima, M. Schuster, 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling pdf

Tara N. Sainath, Ankur Bapna, Navdeep Jaitly, 2019, ArXiv.

Deep Learning for Acoustic Modeling in Parametric Speech Generation: A systematic review of existing techniques and future trends

Heiga Zen, Li Deng, Zhen-Hua Ling, 2015, IEEE Signal Processing Magazine.

Memory-efficient LVCSR search using a one-pass stack decoder

Mike Schuster, 2000, Comput. Speech Lang..

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems pdf

Martín Abadi, Martin Wattenberg, Michael Isard, 2016, ArXiv.

Bi-directional recurrent neural networks for speech recognition

Mike Schuster, M. Schuster, 1996 .

On supervised learning from sequential data with applications for speech regognition

Mike Schuster, M. Schuster, 1999 .

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation pdf

George Kurian, Wei Wang, Quoc V. Le, 2016, ArXiv.

Dynamic planar map lllustration

Mike Schuster, Paul Asente, 2005, SIGGRAPH '05.

A new approach to video sequence recognition based on statistical methods

Gerhard Rigoll, Andreas Kosmala, Mike Schuster, 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

Exploring the Limits of Language Modeling pdf

Yonghui Wu, Oriol Vinyals, Noam Shazeer, 2016, ArXiv.

Speech Recognition for Mobile Devices at Google

Mike Schuster, M. Schuster, 2010, PRICAI.

Statistical parametric speech synthesis using deep neural networks

Heiga Zen, Andrew W. Senior, Mike Schuster, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

High Performance Gesture Recognition Using Probabilistic Neural Networks and Hidden Markov Models

A. Kosmala, G. Rigoll, Mike Schuster, 1997 .

Phoneme boundary estimation using bidirectional recurrent neural networks and its applications

Yoshinori Sagisaka, Mike Schuster, Toshiaki Fukada, 1999, Systems and Computers in Japan.

Mixtures of Probabilistic Principal Component Analyzers in Speech Recognition

Atsushi Nakamura, Takaaki Hori, Mike Schuster, 2004 .

Incorporation of HMM output constraints in hybrid NN/HMM systems during training

Mike Schuster, M. Schuster, 1997, EUROSPEECH.

Deploying GOOG-411: Early lessons in data, measurement, and testing

Johan Schalkwyk, Michiel Bacchiani, Mike Schuster, 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

Reward Augmented Maximum Likelihood for Neural Structured Prediction

Dale Schuurmans, Samy Bengio, Navdeep Jaitly, 2016, NIPS.