Christoph Boeddeker
Christoph Boeddeker
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CHiME-6 challenge: Tackling multispeaker speech recognition for unsegmented recordings
S Watanabe, M Mandel, J Barker, E Vincent, A Arora, X Chang, ...
arXiv preprint arXiv:2004.09249, 2020
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
Front-end processing for the CHiME-5 dinner party scenario
C Boeddeker, J Heitkaemper, J Schmalenstroeer, L Drude, J Heymann, ...
CHiME5 Workshop, Hyderabad, India, 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
Exploring Practical Aspects of Neural Mask-Based Beamforming for Far-Field Speech Recognition
C Boeddeker, H Erdogan, T Yoshioka, R Haeb-Umbach
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
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
Guided Source Separation Meets a Strong ASR Backend: Hitachi/Paderborn University Joint Investigation for Dinner Party ASR
N Kanda, C Boeddeker, J Heitkaemper, Y Fujita, S Horiguchi, ...
arXiv preprint arXiv:1905.12230, 2019
ESPnet-SE: end-to-end speech enhancement and separation toolkit designed for ASR integration
C Li, J Shi, W Zhang, AS Subramanian, X Chang, N Kamo, M Hira, ...
2021 IEEE Spoken Language Technology Workshop (SLT), 785-792, 2021
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
Jointly optimal denoising, dereverberation, and source separation
T Nakatani, C Boeddeker, K Kinoshita, R Ikeshita, M Delcroix, ...
IEEE/ACM Transactions on Audio, Speech, and Language Processing 28, 2267-2282, 2020
Multi-talker ASR for an unknown number of sources: Joint training of source counting, separation and ASR
T von Neumann, C Boeddeker, L Drude, K Kinoshita, M Delcroix, ...
arXiv preprint arXiv:2006.02786, 2020
An investigation into the effectiveness of enhancement in asr training and test for chime-5 dinner party transcription
C Zorilă, C Boeddeker, R Doddipatla, R Haeb-Umbach
2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 47-53, 2019
Jointly optimal dereverberation and beamforming
C Boeddeker, T Nakatani, K Kinoshita, R Haeb-Umbach
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
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
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
End-to-end training of time domain audio separation and recognition
T von Neumann, K Kinoshita, L Drude, C Boeddeker, M Delcroix, ...
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
End-to-end dereverberation, beamforming, and speech recognition with improved numerical stability and advanced frontend
W Zhang, C Boeddeker, S Watanabe, T Nakatani, M Delcroix, K Kinoshita, ...
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
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
Monaural source separation: From anechoic to reverberant environments
T Cord-Landwehr, C Boeddeker, T Von Neumann, C Zorilă, R Doddipatla, ...
2022 International Workshop on Acoustic Signal Enhancement (IWAENC), 1-5, 2022
Graph-PIT: Generalized permutation invariant training for continuous separation of arbitrary numbers of speakers
T von Neumann, K Kinoshita, C Boeddeker, M Delcroix, R Haeb-Umbach
arXiv preprint arXiv:2107.14446, 2021
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