Lukas Drude
Lukas Drude
Applied Scientist @ Amazon
Verified email at - Homepage
Cited by
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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
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
Photovoltaics (PV) and electric vehicle-to-grid (V2G) strategies for peak demand reduction in urban regions in Brazil in a smart grid environment
L Drude, LCP Junior, R Rüther
Renewable Energy 68, 443-451, 2014
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
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
Wide residual BLSTM network with discriminative speaker adaptation for robust speech recognition
LD Jahn Heymann, R Haeb-Umbach
CHiME 2016 workshop 78, 79, 2016
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
Listening to each speaker one by one with recurrent selective hearing networks
K Kinoshita, L Drude, M Delcroix, T Nakatani
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
Tight Integration of Spatial and Spectral Features for BSS with Deep Clustering Embeddings.
L Drude, R Haeb-Umbach
Interspeech, 2650-2654, 2017
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
The RWTH/UPB/FORTH system combination for the 4th CHiME challenge evaluation
T Menne, J Heymann, A Alexandridis, K Irie, A Zeyer, M Kitza, P Golik, ...
Universitätsbibliothek der RWTH Aachen, 2016
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
Source counting in speech mixtures using a variational EM approach for complex Watson mixture models
L Drude, A Chinaev, DHT Vu, R Haeb-Umbach
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
SMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition
L Drude, J Heitkaemper, C Boeddeker, R Haeb-Umbach
arXiv preprint arXiv:1910.13934, 2019
Deep attractor networks for speaker re-identification and blind source separation
L Drude, T von Neumann, R Haeb-Umbach
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
Integration of neural networks and probabilistic spatial models for acoustic blind source separation
L Drude, R Haeb-Umbach
IEEE Journal of Selected Topics in Signal Processing 13 (4), 815-826, 2019
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
Directional statistics and filtering using libDirectional
G Kurz, I Gilitschenski, F Pfaff, L Drude, UD Hanebeck, R Haeb-Umbach, ...
arXiv preprint arXiv:1712.09718, 2017
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
Demystifying TasNet: A dissecting approach
J Heitkaemper, D Jakobeit, C Boeddeker, L Drude, R Haeb-Umbach
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
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