Erik McDermott
Erik McDermott
Machine Learning Researcher, Apple Inc.
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Cited by
Cited by
Deep neural networks for small footprint text-dependent speaker verification
E Variani, X Lei, E McDermott, IL Moreno, J Gonzalez-Dominguez
2014 IEEE international conference on acoustics, speech and signal …, 2014
Transformer transducer: A streamable speech recognition model with transformer encoders and rnn-t loss
Q Zhang, H Lu, H Sak, A Tripathi, E McDermott, S Koo, S Kumar
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
Speech production knowledge in automatic speech recognition
S King, J Frankel, K Livescu, E McDermott, K Richmond, M Wester
The Journal of the Acoustical Society of America 121 (2), 723-742, 2007
Large scale deep neural network acoustic modeling with semi-supervised training data for YouTube video transcription
H Liao, E McDermott, A Senior
2013 IEEE Workshop on Automatic Speech Recognition and Understanding, 368-373, 2013
Discriminative training for large-vocabulary speech recognition using minimum classification error
E McDermott, TJ Hazen, J Le Roux, A Nakamura, S Katagiri
IEEE Transactions on Audio, Speech, and Language Processing 15 (1), 203-223, 2006
Acoustic Modeling for Google Home.
B Li, TN Sainath, A Narayanan, J Caroselli, M Bacchiani, A Misra, ...
Interspeech, 399-403, 2017
Sequence discriminative distributed training of long short-term memory recurrent neural networks
H Sak, O Vinyals, G Heigold, A Senior, E McDermott, R Monga, M Mao
entropy 15 (16), 17-18, 2014
Asynchronous optimization for sequence training of neural networks
G Heigold, E McDermott, VO Vanhoucke, AW Senior, MAU Bacchiani
US Patent 10,019,985, 2018
An application of discriminative feature extraction to filter-bank-based speech recognition
A Biem, S Katagiri, E McDermott, BH Juang
IEEE Transactions on Speech and Audio Processing 9 (2), 96-110, 2001
A density ratio approach to language model fusion in end-to-end automatic speech recognition
E McDermott, H Sak, E Variani
2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU …, 2019
Shift-invariant, multi-category phoneme recognition using Kohonen's LVQ2
E McDermott, S Katagiri
International Conference on Acoustics, Speech, and Signal Processing,, 81-84, 1989
Discriminative training for speech recognition
E McDermott
Waseda University, 1997
Asynchronous stochastic optimization for sequence training of deep neural networks
G Heigold, E McDermott, V Vanhoucke, A Senior, M Bacchiani
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
A Gaussian mixture model layer jointly optimized with discriminative features within a deep neural network architecture
E Variani, E McDermott, G Heigold
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
A hybrid speech recognition system using HMMs with an LVQ-trained codebook
H Iwamida, S Katagiri, E McDermott, Y Tohkura
Journal of the Acoustical Society of Japan (E) 11 (5), 277-286, 1990
Speaker verification using neural networks
X Lei, E McDermott, E Variani, IL Moreno
US Patent 9,401,148, 2016
Prototype-based minimum classification error/generalized probabilistic descent training for various speech units
E McDermott, S Katagiri
Computer Speech & Language 8 (4), 351-368, 1994
LVQ-based shift-tolerant phoneme recognition
E McDermott, S Katagiri
IEEE Transactions on Signal Processing 39 (6), 1398-1411, 1991
Training conditional random fields with multivariate evaluation measures
J Suzuki, E McDermott, H Isozaki
Proceedings of the 21st International Conference on Computational …, 2006
Computer-based second language production training by using spectrographic representation and HMM-based speech recognition scores
R Akahane-Yamada, E McDermott, T Adachi, H Kawahara, JS Pruitt
Fifth International Conference on Spoken Language Processing, 1998
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