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 | 1373 | 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 | 550 | 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 | 255 | 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 | 251 | 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 | 216 | 2006 |
Acoustic Modeling for Google Home. B Li, TN Sainath, A Narayanan, J Caroselli, M Bacchiani, A Misra, ... Interspeech, 399-403, 2017 | 205 | 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 | 172 | 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 | 149 | 2018 |
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 | 120 | 2019 |
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 | 117 | 2001 |
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 | 102 | 1989 |
Discriminative training for speech recognition E McDermott Waseda University, 1997 | 95 | 1997 |
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 | 79 | 2015 |
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 | 76 | 2014 |
Speaker verification using neural networks X Lei, E McDermott, E Variani, IL Moreno US Patent 9,401,148, 2016 | 74 | 2016 |
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 | 74 | 1990 |
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 | 70 | 1994 |
LVQ-based shift-tolerant phoneme recognition E McDermott, S Katagiri IEEE Transactions on Signal Processing 39 (6), 1398-1411, 1991 | 65 | 1991 |
Training conditional random fields with multivariate evaluation measures J Suzuki, E McDermott, H Isozaki Proceedings of the 21st International Conference on Computational …, 2006 | 63 | 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 | 55 | 1998 |