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Timo Gerkmann
Timo Gerkmann
Signal Processing, Computer Science Department, Universität Hamburg, Germany
Verified email at uni-hamburg.de - Homepage
Title
Cited by
Cited by
Year
Unbiased MMSE-based noise power estimation with low complexity and low tracking delay
T Gerkmann, RC Hendriks
IEEE Transactions on Audio, Speech, and Language Processing 20 (4), 1383-1393, 2011
6442011
Phase processing for single-channel speech enhancement: History and recent advances
T Gerkmann, M Krawczyk-Becker, J Le Roux
IEEE signal processing Magazine 32 (2), 55-66, 2015
2602015
STFT phase reconstruction in voiced speech for an improved single-channel speech enhancement
M Krawczyk, T Gerkmann
IEEE/ACM Transactions on Audio, Speech, and Language Processing 22 (12 …, 2014
2302014
DFT-domain based single-microphone noise reduction for speech enhancement
RC Hendriks, T Gerkmann, J Jensen
Morgan & Claypool Publishers, 2013
1952013
A novel a priori SNR estimation approach based on selective cepstro-temporal smoothing
C Breithaupt, T Gerkmann, R Martin
2008 IEEE International Conference on Acoustics, Speech and Signal …, 2008
1622008
Noise power estimation based on the probability of speech presence
T Gerkmann, RC Hendriks
2011 IEEE Workshop on Applications of Signal Processing to Audio and …, 2011
1562011
Improved A Posteriori Speech Presence Probability Estimation Based on a Likelihood Ratio With Fixed Priors
T Gerkmann, C Breithaupt, R Martin
IEEE transactions on audio, speech, and language processing 16 (5), 910-919, 2008
1262008
Multi-channel linear prediction-based speech dereverberation with sparse priors
A Jukić, T van Waterschoot, T Gerkmann, S Doclo
IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (9), 1509 …, 2015
1252015
Cepstral smoothing of spectral filter gains for speech enhancement without musical noise
C Breithaupt, T Gerkmann, R Martin
IEEE Signal processing letters 14 (12), 1036-1039, 2007
1092007
Combination of MVDR beamforming and single-channel spectral processing for enhancing noisy and reverberant speech
B Cauchi, I Kodrasi, R Rehr, S Gerlach, A Jukić, T Gerkmann, S Doclo, ...
EURASIP Journal on Advances in Signal Processing 2015, 1-12, 2015
902015
Noise correlation matrix estimation for multi-microphone speech enhancement
RC Hendriks, T Gerkmann
IEEE Transactions on Audio, Speech, and Language Processing 20 (1), 223-233, 2011
892011
Speech enhancement and dereverberation with diffusion-based generative models
J Richter, S Welker, JM Lemercier, B Lay, T Gerkmann
IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2023
842023
MMSE-optimal spectral amplitude estimation given the STFT-phase
T Gerkmann, M Krawczyk
IEEE Signal Processing Letters 20 (2), 129-132, 2012
812012
On the statistics of spectral amplitudes after variance reduction by temporal cepstrum smoothing and cepstral nulling
T Gerkmann, R Martin
IEEE Transactions on Signal Processing 57 (11), 4165-4174, 2009
772009
A multi-phase gammatone filterbank for speech separation via tasnet
D Ditter, T Gerkmann
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
732020
A new linear MMSE filter for single channel speech enhancement based on nonnegative matrix factorization
N Mohammadiha, T Gerkmann, A Leijon
2011 IEEE workshop on applications of signal processing to audio and …, 2011
702011
Speech Enhancement with Score-Based Generative Models in the Complex STFT Domain
S Welker, J Richter, T Gerkmann
Proc. Interspeech 2022, 2928 - 2932, 2022
652022
Comparing binaural pre-processing strategies II: Speech intelligibility of bilateral cochlear implant users
RM Baumgärtel, H Hu, M Krawczyk-Becker, D Marquardt, T Herzke, ...
Trends in hearing 19, 2331216515617917, 2015
632015
Bayesian estimation of clean speech spectral coefficients given a priori knowledge of the phase
T Gerkmann
IEEE Transactions on Signal Processing 62 (16), 4199-4208, 2014
532014
Variational autoencoder for speech enhancement with a noise-aware encoder
H Fang, G Carbajal, S Wermter, T Gerkmann
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
512021
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