Reinhold Haeb-Umbach

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Lukas DrudeApplied Scientist @ Amazon AlexaEmail confirmado em amazon.com
Christoph BoeddekerPaderborn UniversityEmail confirmado em mail.upb.de
Joerg SchmalenstroeerDepartment of Communications Engineering, University of PaderbornEmail confirmado em nt.uni-paderborn.de
Jahn HeymannApplied Scientist @ AmazonEmail confirmado em amazon.com
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Marc DelcroixNTT Communication Science LaboratoriesEmail confirmado em ieee.org
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Hermann NeyRWTH Aachen UniversityEmail confirmado em cs.rwth-aachen.de
Bhiksha RajCarnegie Mellon UniversityEmail confirmado em cs.cmu.edu
Oliver WalterTeam Lead and Research Engineer, Business Unit Speech Technologies, Fraunhofer IAISEmail confirmado em iais.fraunhofer.de
Janek EbbersPaderborn UniversityEmail confirmado em nt.upb.de
Aleksej ChinaevDevision for Speech Technology and Hearing Aids, Carl-von-Ossietzky University of Oldenburg (GermanyEmail confirmado em uol.de
Peter BeyerleinProfessor of Bioinformatics, University of Applied Sciences WildauEmail confirmado em th-wildau.de
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Armin SehrOTH RegensburgEmail confirmado em oth-regensburg.de
Sharon GannotProf. of Electrical Engineering, Bar-Ilan University, IsraelEmail confirmado em biu.ac.il
Roland MaasSr. Science Manager at AmazonEmail confirmado em amazon.com
Emanuël HabetsInternational Audio Laboratories Erlangen, GermanyEmail confirmado em ieee.org
Marco LoogRadboud UniversityEmail confirmado em ru.nl

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Reinhold Haeb-Umbach

Professor of Communications Engineering, University of Paderborn

Email confirmado em nt.uni-paderborn.de - Página inicial

automatic speech recognition speech enhancement statistical signal processing


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
An overview of noise-robust automatic speech recognition J Li, L Deng, Y Gong, R Haeb-Umbach IEEE/ACM Transactions on Audio, Speech, and Language Processing 22 (4), 745-777, 2014	621	2014
Multi-class Linear Dimension Reduction by Weighted Pairwise Fisher Criteria M Loog, RPW Duin, R Haeb-Umbach IEEE Transactions on Pattern Analysis and Machine Intelligence 23 (7), 2001	608	2001
Linear discriminant analysis for improved large vocabulary continuous speech recognition. R Haeb-Umbach, H Ney icassp 92, 13-16, 1992	515	1992
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	487	2016
The REVERB Challenge: A Common Evaluation Framework for Dereverberation and Recognition of Reverberant Speech K Kinoshita, M Delcroix, T Yoshioka, T Nakatani, E Habets, ... IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2013	439	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	393	2016
Improvements in beam search for 10000-word continuous speech recognition H Ney, R Haeb-Umbach, BH Tran, M Oerder [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics …, 1992	290	1992
Blind acoustic beamforming based on generalized eigenvalue decomposition E Warsitz, R Haeb-Umbach IEEE Transactions on audio, speech, and language processing 15 (5), 1529-1539, 2007	257	2007
Robust automatic speech recognition: a bridge to practical applications J Li, L Deng, R Haeb-Umbach, Y Gong Academic Press, 2015	189	2015
A Systematic Approach to Carrier Recovery and Detection of Digitally Phase Modulated Signals on Fading Channels R Haeb, H Meyr IEEE Transactions on Communications 37 (7), 748-754, 1989	173	1989
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	167	2015
Speech processing for digital home assistants: Combining signal processing with deep-learning techniques R Haeb-Umbach, S Watanabe, T Nakatani, M Bacchiani, B Hoffmeister, ... IEEE Signal processing magazine 36 (6), 111-124, 2019	151	2019
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	131	2017
Improvements in beam search for 10000-word continuous-speech recognition R Haeb-Umbach, H Ney IEEE Transactions on Speech and Audio Processing 2 (2), 353-356, 1994	106	1994
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	105	2018
Blind speech separation employing directional statistics in an expectation maximization framework DHT Vu, R Haeb-Umbach 2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010	105	2010
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	98	2018
All-neural online source separation, counting, and diarization for meeting analysis T Von Neumann, K Kinoshita, M Delcroix, S Araki, T Nakatani, ... ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019	96	2019
European speech databases for telephone applications H Hoge, HS Tropf, R Winski, H van den Heuvel, R Haeb-Umbach, ... 1997 IEEE International Conference on Acoustics, Speech, and Signal …, 1997	96	1997
Improvements in connected digit recognition using linear discriminant analysis and mixture densities R Haeb-Umbach, D Geller, H Ney 1993 IEEE International Conference on Acoustics, Speech, and Signal …, 1993	96	1993

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