| 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 | 4024 | 2016 |
| 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 | 264 | 2018 |
| Lattice Minimum Bayes-Risk decoding for statistical machine translation R Tromble, S Kumar, FJ Och, W Macherey Proceedings of the 2008 Conference on Empirical Methods in Natural Language …, 2008 | 140 | 2008 |
| Comparison of discriminative training criteria and optimization methods for speech recognition R Schlüter, W Macherey, B Müller, H Ney Speech Communication 34 (3), 287-310, 2001 | 127 | 2001 |
| Lattice-based minimum error rate training for statistical machine translation W Macherey, F Och, I Thayer, J Uszkoreit | 123 | 2008 |
| Investigations on error minimizing training criteria for discriminative training in automatic speech recognition W Macherey, L Haferkamp, R Schlüter, H Ney Ninth European Conference on Speech Communication and Technology, 2005 | 101 | 2005 |
| Efficient Minimum Error Rate Training and Minimum Bayes-Risk Decoding for Translation Hypergraphs and Lattices S Kumar, W Macherey, C Dyer, F Och | 95 | 2009 |
| 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 | 82 | 2019 |
| Massively multilingual neural machine translation in the wild: Findings and challenges N Arivazhagan, A Bapna, O Firat, D Lepikhin, M Johnson, M Krikun, ... arXiv preprint arXiv:1907.05019, 2019 | 80 | 2019 |
| Adaptation in statistical pattern recognition using tangent vectors D Keysers, W Macherey, H Ney, J Dahmen IEEE Transactions on Pattern Analysis and Machine Intelligence 26 (2), 269-274, 2004 | 80 | 2004 |
| 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 | 79 | 2016 |
| Robust neural machine translation with doubly adversarial inputs Y Cheng, L Jiang, W Macherey arXiv preprint arXiv:1906.02443, 2019 | 74 | 2019 |
| Comparison of discriminative training criteria R Schluter, W Macherey Proceedings of the 1998 IEEE International Conference on Acoustics, Speech …, 1998 | 74 | 1998 |
| FIRE in ImageCLEF 2005: Combining content-based image retrieval with textual information retrieval T Deselaers, T Weyand, D Keysers, W Macherey, H Ney Workshop of the Cross-Language Evaluation Forum for European Languages, 652-661, 2005 | 72 | 2005 |
| Leveraging weakly supervised data to improve end-to-end speech-to-text translation Y Jia, M Johnson, W Macherey, RJ Weiss, Y Cao, CC Chiu, N Ari, ... ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 68 | 2019 |
| Improving word alignment with bridge languages S Kumar, F Och, W Macherey | 66 | 2007 |
| Revisiting character-based neural machine translation with capacity and compression C Cherry, G Foster, A Bapna, O Firat, W Macherey arXiv preprint arXiv:1808.09943, 2018 | 60 | 2018 |
| Monotonic infinite lookback attention for simultaneous machine translation N Arivazhagan, C Cherry, W Macherey, CC Chiu, S Yavuz, R Pang, W Li, ... arXiv preprint arXiv:1906.05218, 2019 | 55 | 2019 |
| Google’s neural machine translation system: Bridging the gap between human and machine translation. CoRR abs/1609.08144 (2016) Y Wu, M Schuster, Z Chen, QV Le, M Norouzi, W Macherey, M Krikun, ... arXiv preprint arXiv:1609.08144, 2016 | 51 | 2016 |
| An empirical study on computing consensus translations from multiple machine translation systems W Macherey, FJ Och | 51 | 2007 |
