| The REVERB challenge: A common evaluation framework for dereverberation and recognition of reverberant speech K Kinoshita, M Delcroix, T Yoshioka, T Nakatani, E Habets, ... 2013 IEEE Workshop on Applications of Signal Processing to Audio and …, 2013 | 483 | 2013 |
| A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research K Kinoshita, M Delcroix, S Gannot, EA P. Habets, R Haeb-Umbach, ... EURASIP Journal on Advances in Signal Processing 2016, 1-19, 2016 | 427 | 2016 |
| Making machines understand us in reverberant rooms: Robustness against reverberation for automatic speech recognition T Yoshioka, A Sehr, M Delcroix, K Kinoshita, R Maas, T Nakatani, ... IEEE Signal Processing Magazine 29 (6), 114-126, 2012 | 342 | 2012 |
| Speech and audio processing in adverse environments GS Eberhard Hänsler Springer Science & Business Media, 2008 | 140* | 2008 |
| Speech and audio processing in adverse environments G Schmidt | 113* | 2008 |
| Reverberation model-based decoding in the logmelspec domain for robust distant-talking speech recognition A Sehr, R Maas, W Kellermann IEEE transactions on audio, speech, and language processing 18 (7), 1676-1691, 2010 | 81 | 2010 |
| A stereophonic acoustic signal extraction scheme for noisy and reverberant environments K Reindl, Y Zheng, A Schwarz, S Meier, R Maas, A Sehr, W Kellermann Computer Speech & Language 27 (3), 726-745, 2013 | 45 | 2013 |
| Towards a better understanding of the effect of reverberation on speech recognition performance A Sehr, EAP Habets, R Maas, W Kellermann Proc. IWAENC, 1-4, 2010 | 39 | 2010 |
| On the application of reverberation suppression to robust speech recognition R Maas, EAP Habets, A Sehr, W Kellermann 2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012 | 28 | 2012 |
| A two-channel acoustic front-end for robust automatic speech recognition in noisy and reverberant environments R Maas, A Schwarz, Y Zheng, K Reindl, S Meier, A Sehr, W Kellermann Machine Listening in Multisource Environments, 2011 | 26 | 2011 |
| Distant-talking continuous speech recognition based on a novel reverberation model in the feature domain. A Sehr, M Zeller, W Kellermann INTERSPEECH, 2006 | 24 | 2006 |
| Reverberation Modeling for Robust Distant Talking Speech Recognition: Nachhallmodellierung Für Die Robuste Spracherkennung Mit Freisprechmikrofonen AM Sehr Verlag Dr. Hut, 2010 | 23 | 2010 |
| A new concept for feature-domain dereverberation for robust distant-talking asr A Sehr, W Kellermann 2007 IEEE International Conference on Acoustics, Speech and Signal …, 2007 | 22 | 2007 |
| A novel approach for matched reverberant training of HMMs using data pairs. A Sehr, C Hofmann, R Maas, W Kellermann INTERSPEECH, 566-569, 2010 | 15 | 2010 |
| Hands-free speech recognition using a reverberation model in the feature domain A Sehr, M Zeller, W Kellermann 2006 14th European Signal Processing Conference, 1-5, 2006 | 14 | 2006 |
| Frame-wise HMM adaptation using state-dependent reverberation estimates A Sehr, R Maas, W Kellermann 2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011 | 13 | 2011 |
| On the statistical properties of reverberant speech feature vector sequences A Sehr, W Kellermann Proc. Int. Workshop on Acoustic Echo and Noise Control (IWAENC), 2010 | 12 | 2010 |
| The REVERB challenge: A benchmark task for reverberation-robust ASR techniques K Kinoshita, M Delcroix, S Gannot, EAP Habets, R Haeb-Umbach, ... New Era for Robust Speech Recognition: Exploiting Deep Learning, 345-354, 2017 | 11 | 2017 |
| Multi-style training of HMMs with stereo data for reverberation-robust speech recognition A Sehr, C Hofmann, R Maas, W Kellermann 2011 Joint Workshop on Hands-free Speech Communication and Microphone Arrays …, 2011 | 10 | 2011 |
| Maximum likelihood estimation of a reverberation model for robust distant-talking speech recognition A Sehr, Y Zheng, E Nöth, W Kellermann 2007 15th European Signal Processing Conference, 1299-1303, 2007 | 10 | 2007 |
Roland MaasSr. Science Manager at AmazonVerified email at amazon.com
