| 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 | 421 | 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 | 368 | 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 | 320 | 2012 |
| Anchored speech detection and speech recognition SHK Parthasarathi, B Hoffmeister, B King, R Maas US Patent 10,373,612, 2019 | 224 | 2019 |
| 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 | 80 | 2010 |
| Improving noise robustness of automatic speech recognition via parallel data and teacher-student learning L Mošner, M Wu, A Raju, SHK Parthasarathi, K Kumatani, S Sundaram, ... ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 53 | 2019 |
| 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 | 46 | 2013 |
| Spatial diffuseness features for DNN-based speech recognition in noisy and reverberant environments A Schwarz, C Huemmer, R Maas, W Kellermann 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 44 | 2015 |
| Device-directed utterance detection SH Mallidi, R Maas, K Goehner, A Rastrow, S Matsoukas, B Hoffmeister arXiv preprint arXiv:1808.02504, 2018 | 43 | 2018 |
| Efficient minimum word error rate training of RNN-Transducer for end-to-end speech recognition J Guo, G Tiwari, J Droppo, M Van Segbroeck, CW Huang, A Stolcke, ... arXiv preprint arXiv:2007.13802, 2020 | 40 | 2020 |
| 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 | 37 | 2010 |
| Robust speech recognition via anchor word representations B King, IF Chen, Y Vaizman, Y Liu, R Maas, SHK Parthasarathi, ... | 33 | 2017 |
| Improving ASR confidence scores for Alexa using acoustic and hypothesis embeddings P Swarup, R Maas, S Garimella, SH Mallidi, B Hoffmeister | 31 | 2019 |
| 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 | 27 | 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 |
| The elitist particle filter based on evolutionary strategies as novel approach for nonlinear acoustic echo cancellation C Huemmer, C Hofmann, R Maas, A Schwarz, W Kellermann 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 25 | 2014 |
| Wav2vec-c: A self-supervised model for speech representation learning S Sadhu, D He, CW Huang, SH Mallidi, M Wu, A Rastrow, A Stolcke, ... arXiv preprint arXiv:2103.08393, 2021 | 24 | 2021 |
| The NLMS algorithm with time-variant optimum stepsize derived from a Bayesian network perspective C Huemmer, R Maas, W Kellermann IEEE Signal Processing Letters 22 (11), 1874-1878, 2015 | 22 | 2015 |
| Combining acoustic embeddings and decoding features for end-of-utterance detection in real-time far-field speech recognition systems R Maas, A Rastrow, C Ma, G Lan, K Goehner, G Tiwari, S Joseph, ... 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 21 | 2018 |
| A Study for Improving Device-Directed Speech Detection Toward Frictionless Human-Machine Interaction. CW Huang, R Maas, SH Mallidi, B Hoffmeister INTERSPEECH, 3342-3346, 2019 | 20 | 2019 |
Armin SehrOTH RegensburgΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα oth-regensburg.de
