| {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 (OSDI …, 2016 | 55147* | 2016 |
| Bidirectional recurrent neural networks M Schuster, KK Paliwal IEEE transactions on Signal Processing 45 (11), 2673-2681, 1997 | 10765 | 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 | 8747 | 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 | 3115 | 2018 |
| 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 | 2330 | 2017 |
| Exploring the limits of language modeling R Jozefowicz, O Vinyals, M Schuster, N Shazeer, Y Wu arXiv preprint arXiv:1602.02410, 2016 | 1396 | 2016 |
| 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 | 1257 | 2013 |
| Statistical parametric speech synthesis using deep neural networks H Zen, A Senior, M Schuster 2013 ieee international conference on acoustics, speech and signal …, 2013 | 1149 | 2013 |
| Japanese and korean voice search M Schuster, K Nakajima 2012 IEEE international conference on acoustics, speech and signal …, 2012 | 1128 | 2012 |
| 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 | 525 | 2018 |
| 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 52, 2015 | 498 | 2015 |
| Tensorflow: Large-scale machine learning on heterogeneous distributed systems. CoRR abs/1603.04467 (2016) M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... arXiv preprint arXiv:1603.04467, 2016 | 325 | 2016 |
| Speech synthesis using deep neural networks AW Senior, B Chun, M Schuster US Patent 8,527,276, 2013 | 297 | 2013 |
| 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 | 296 | 2015 |
| TensorFlow: Large-scale machine learning on heterogeneous systems (2015), software available from tensorflow. org M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... | 284 | 2019 |
| 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, 2016 | 252 | 2016 |
| Systems and Methods for Designing Voice Applications M Schuster US Patent App. 13/608,193, 2015 | 229 | 2015 |
| 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 | 204 | 2019 |
| Large-scale machine learning on heterogeneous distributed systems M Abadi, AABP TensorFlow Proceedings of the 12th USENIX symposium on operating systems design and …, 2016 | 199 | 2016 |
| TensorFlow: Large-scale machine learning on heterogeneous systems. arXiv 2015 M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... arXiv preprint arXiv:1603.04467, 2016 | 152 | 2016 |
