| Tensorflow: A system for large-scale machine learning M Abadi, P Barham, J Chen, Z Chen, A Davis, J Dean, M Devin, ... 12th {USENIX} symposium on operating systems design and implementation …, 2016 | 18234* | 2016 |
| TensorFlow: Large-scale machine learning on heterogeneous systems M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... | 8426 | 2015 |
| Bidirectional recurrent neural networks M Schuster, KK Paliwal IEEE transactions on Signal Processing 45 (11), 2673-2681, 1997 | 4731 | 1997 |
| Google's neural machine translation system: Bridging the gap between human and machine translation Y Wu, M Schuster, Z Chen, QV Le, M Norouzi, W Macherey, M Krikun, ... arXiv preprint arXiv:1609.08144, 2016 | 3819 | 2016 |
| Google’s multilingual neural machine translation system: Enabling zero-shot translation M Johnson, M Schuster, QV Le, M Krikun, Y Wu, Z Chen, N Thorat, ... Transactions of the Association for Computational Linguistics 5, 339-351, 2017 | 1113 | 2017 |
| Google’s multilingual neural machine translation system: Enabling zero-shot translation M Johnson, M Schuster, QV Le, M Krikun, Y Wu, Z Chen, N Thorat, ... Transactions of the Association for Computational Linguistics 5, 339-351, 2017 | 1113 | 2017 |
| Exploring the limits of language modeling R Jozefowicz, O Vinyals, M Schuster, N Shazeer, Y Wu arXiv preprint arXiv:1602.02410, 2016 | 879 | 2016 |
| Natural tts synthesis by conditioning wavenet on mel spectrogram predictions J Shen, R Pang, RJ Weiss, M Schuster, N Jaitly, Z Yang, Z Chen, Y Zhang, ... 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 842 | 2018 |
| Statistical parametric speech synthesis using deep neural networks H Ze, A Senior, M Schuster 2013 ieee international conference on acoustics, speech and signal …, 2013 | 826 | 2013 |
| One billion word benchmark for measuring progress in statistical language modeling C Chelba, T Mikolov, M Schuster, Q Ge, T Brants, P Koehn, T Robinson arXiv preprint arXiv:1312.3005, 2013 | 796 | 2013 |
| Japanese and korean voice search M Schuster, K Nakajima 2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012 | 310 | 2012 |
| TensorFlow: Large-scale machine learning on heterogeneous systems, software available from tensorflow. org (2015) M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... URL https://www. tensorflow. org, 2015 | 302 | 2015 |
| The best of both worlds: Combining recent advances in neural machine translation MX Chen, O Firat, A Bapna, M Johnson, W Macherey, G Foster, L Jones, ... arXiv preprint arXiv:1804.09849, 2018 | 257 | 2018 |
| Deep learning for acoustic modeling in parametric speech generation: A systematic review of existing techniques and future trends ZH Ling, SY Kang, H Zen, A Senior, M Schuster, XJ Qian, HM Meng, ... IEEE Signal Processing Magazine 32 (3), 35-52, 2015 | 221 | 2015 |
| Tensorflow: large-scale machine learning on heterogeneous distributed systems (2016) M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... arXiv preprint arXiv:1603.04467 172, 2015 | 196 | 2015 |
| Reward augmented maximum likelihood for neural structured prediction M Norouzi, S Bengio, N Jaitly, M Schuster, Y Wu, D Schuurmans Advances In Neural Information Processing Systems 29, 1723-1731, 2016 | 148 | 2016 |
| Speech recognition for mobile devices at Google M Schuster Pacific Rim International Conference on Artificial Intelligence, 8-10, 2010 | 82 | 2010 |
| ukasz Kaiser Y Wu, M Schuster, Z Chen, QV Le, M Norouzi, W Macherey, M Krikun, ... Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens …, 2016 | 78 | 2016 |
| Lingvo: a modular and scalable framework for sequence-to-sequence modeling J Shen, P Nguyen, Y Wu, Z Chen, MX Chen, Y Jia, A Kannan, T Sainath, ... arXiv preprint arXiv:1902.08295, 2019 | 73 | 2019 |
| Deploying GOOG-411: Early lessons in data, measurement, and testing M Bacchiani, F Beaufays, J Schalkwyk, M Schuster, B Strope 2008 IEEE International Conference on Acoustics, Speech and Signal …, 2008 | 63 | 2008 |
