| LSTM neural networks for language modeling M Sundermeyer, R Schlüter, H Ney Thirteenth annual conference of the international speech communication …, 2012 | 1806 | 2012 |
| Confidence measures for large vocabulary continuous speech recognition F Wessel, R Schlüter, K Macherey, H Ney IEEE Transactions on speech and audio processing 9 (3), 288-298, 2001 | 640 | 2001 |
| From feedforward to recurrent LSTM neural networks for language modeling M Sundermeyer, H Ney, R Schlüter IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (3), 517-529, 2015 | 411 | 2015 |
| Computing mel-frequency cepstral coefficients on the power spectrum S Molau, M Pitz, R Schlüter, H Ney Acoustics, Speech, and Signal Processing, 2001. Proceedings.(ICASSP'01 …, 2001 | 339 | 2001 |
| Vocal Tract Normalization Equals Linear Transformation in Cepstral Space. M Pitz, S Molau, R Schlüter, H Ney European Conference on Speech Communication and Technology (EUROSPEECH …, 2001 | 279* | 2001 |
| Improved training of end-to-end attention models for speech recognition A Zeyer, K Irie, R Schlüter, H Ney arXiv preprint arXiv:1805.03294, 2018 | 217 | 2018 |
| Acoustic Modeling with Deep Neural Networks using Raw Time Signal for LVCSR. Z Tüske, P Golik, R Schlüter, H Ney Interspeech, 890-894, 2014 | 193 | 2014 |
| RWTH ASR Systems for LibriSpeech: Hybrid vs Attention--w/o Data Augmentation C Lüscher, E Beck, K Irie, M Kitza, W Michel, A Zeyer, R Schlüter, H Ney arXiv preprint arXiv:1905.03072, 2019 | 175 | 2019 |
| Gammatone Features and Feature Combination for Large Vocabulary Speech Recognition R Schlüter, I Bezrukov, H Wagner, H Ney 2007 IEEE International Conference on Acoustics, Speech and Signal …, 2007 | 173 | 2007 |
| Using Word Probabilities as Confidence Measures F Wessel, K Macherey, R Schlüter Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE …, 1998 | 159 | 1998 |
| A comprehensive study of deep bidirectional LSTM RNNs for acoustic modeling in speech recognition A Zeyer, P Doetsch, P Voigtlaender, R Schlüter, H Ney 2017 IEEE international conference on acoustics, speech and signal …, 2017 | 151 | 2017 |
| Comparison of Feedforward and Recurrent Neural Network Language Models M Sundermeyer, I Oparin, JL Gauvain, B Freiberg, R Schlüter, H Ney Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International …, 2013 | 144 | 2013 |
| The RWTH Aachen University Open Source Speech Recognition System. D Rybach, C Gollan, G Heigold, B Hoffmeister, J Lööf, R Schlüter, H Ney Interspeech, 2111-2114, 2009 | 130 | 2009 |
| 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 |
| Convolutional neural networks for acoustic modeling of raw time signal in LVCSR P Golik, Z Tüske, R Schlüter, H Ney Sixteenth annual conference of the international speech communication …, 2015 | 111 | 2015 |
| Investigations on Error Minimizing Training Criteria for Discriminative Training in Automatic Speech Recognition W Macherey, L Haferkamp, R Schlüter, H Ney Interspeech 2005, 2133-2136, 2005 | 101 | 2005 |
| Acoustic Feature Combination for Robust Speech Recognition A Zolnay, R Schluter, H Ney Acoustics, Speech, and Signal Processing, 2005. Proceedings.(ICASSP'05 …, 2005 | 98 | 2005 |
| RASR-The RWTH Aachen University Open Source Speech Recognition Toolkit D Rybach, S Hahn, P Lehnen, D Nolden, M Sundermeyer, Z Tüske, ... Proc. IEEE Automatic Speech Recognition and Understanding Workshop, 2011 | 90 | 2011 |
| Using Phase Spectrum Information for Improved Speech Recognition Performance R Schlüter, H Ney Acoustics, Speech, and Signal Processing, 2001. Proceedings.(ICASSP'01 …, 2001 | 88 | 2001 |
| Language modeling with deep transformers K Irie, A Zeyer, R Schlüter, H Ney arXiv preprint arXiv:1905.04226, 2019 | 85 | 2019 |
Hermann NeyRWTH Aachen UniversityVerified email at cs.rwth-aachen.de
