Espnet: End-to-end speech processing toolkit S Watanabe, T Hori, S Karita, T Hayashi, J Nishitoba, Y Unno, NEY Soplin, ... arXiv preprint arXiv:1804.00015, 2018 | 1503 | 2018 |
Neural network based spectral mask estimation for acoustic beamforming J Heymann, L Drude, R Haeb-Umbach 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 517 | 2016 |
BLSTM supported GEV beamformer front-end for the 3rd CHiME challenge J Heymann, L Drude, A Chinaev, R Haeb-Umbach 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU …, 2015 | 175 | 2015 |
Beamnet: End-to-end training of a beamformer-supported multi-channel ASR system J Heymann, L Drude, C Boeddeker, P Hanebrink, R Haeb-Umbach 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 139 | 2017 |
Front-end processing for the CHiME-5 dinner party scenario C Boeddeker, J Heitkaemper, J Schmalenstroeer, L Drude, J Heymann, ... CHiME5 Workshop, Hyderabad, India 1, 2018 | 121 | 2018 |
NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing L Drude, J Heymann, C Boeddeker, R Haeb-Umbach Speech Communication; 13th ITG-Symposium, 1-5, 2018 | 112 | 2018 |
Far-field automatic speech recognition R Haeb-Umbach, J Heymann, L Drude, S Watanabe, M Delcroix, ... Proceedings of the IEEE 109 (2), 124-148, 2020 | 101 | 2020 |
Wide residual BLSTM network with discriminative speaker adaptation for robust speech recognition LD Jahn Heymann, R Haeb-Umbach Proceedings of the 4th International Workshop on Speech Processing in …, 2016 | 69 | 2016 |
A generic neural acoustic beamforming architecture for robust multi-channel speech processing J Heymann, L Drude, R Haeb-Umbach Computer Speech & Language 46, 374-385, 2017 | 61 | 2017 |
Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery. J Ebbers, J Heymann, L Drude, T Glarner, R Haeb-Umbach, B Raj InterSpeech, 488-492, 2017 | 52 | 2017 |
The RWTH/UPB/FORTH system combination for the 4th CHiME challenge evaluation T Menne Deutsche Nationalbibliothek, 2016 | 52 | 2016 |
Integrating Neural Network Based Beamforming and Weighted Prediction Error Dereverberation. L Drude, C Boeddeker, J Heymann, R Haeb-Umbach, K Kinoshita, ... Interspeech, 3043-3047, 2018 | 41 | 2018 |
Performance of mask based statistical beamforming in a smart home scenario J Heymann, M Bacchiani, TN Sainath 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 41 | 2018 |
On the computation of complex-valued gradients with application to statistically optimum beamforming C Boeddeker, P Hanebrink, L Drude, J Heymann, R Haeb-Umbach arXiv preprint arXiv:1701.00392, 2017 | 39 | 2017 |
Joint optimization of neural network-based WPE dereverberation and acoustic model for robust online ASR J Heymann, L Drude, R Haeb-Umbach, K Kinoshita, T Nakatani ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 36 | 2019 |
Frame-online DNN-WPE dereverberation J Heymann, L Drude, R Haeb-Umbach, K Kinoshita, T Nakatani 2018 16th International Workshop on Acoustic Signal Enhancement (IWAENC …, 2018 | 35 | 2018 |
Unsupervised training of neural mask-based beamforming L Drude, J Heymann, R Haeb-Umbach arXiv preprint arXiv:1904.01578, 2019 | 32 | 2019 |
Iterative Bayesian word segmentation for unsupervised vocabulary discovery from phoneme lattices J Heymann, O Walter, R Haeb-Umbach, B Raj 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 32 | 2014 |
Unsupervised word segmentation from noisy input J Heymann, O Walter, R Haeb-Umbach, B Raj 2013 IEEE workshop on automatic speech recognition and understanding, 458-463, 2013 | 32 | 2013 |
Multi-stage coherence drift based sampling rate synchronization for acoustic beamforming J Schmalenstroeer, J Heymann, L Drude, C Boeddecker, ... 2017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP …, 2017 | 30 | 2017 |