Roland Maas
Roland Maas
Sr. Scientist at Amazon
Verified email at amazon.com
TitleCited byYear
The REVERB challenge: A common evaluation framework for dereverberation and recognition of reverberant speech
K Kinoshita, M Delcroix, T Yoshioka, T Nakatani, E Habets, ...
2013 IEEE Workshop on Applications of Signal Processing to Audio and†…, 2013
2692013
Making machines understand us in reverberant rooms: Robustness against reverberation for automatic speech recognition
T Yoshioka, A Sehr, M Delcroix, K Kinoshita, R Maas, T Nakatani, ...
IEEE Signal Processing Magazine 29 (6), 114-126, 2012
2062012
A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research
K Kinoshita, M Delcroix, S Gannot, EAP Habets, R Haeb-Umbach, ...
EURASIP Journal on Advances in Signal Processing 2016 (1), 7, 2016
1412016
Reverberation model-based decoding in the logmelspec domain for robust distant-talking speech recognition
A Sehr, R Maas, W Kellermann
IEEE transactions on audio, speech, and language processing 18 (7), 1676-1691, 2010
722010
A stereophonic acoustic signal extraction scheme for noisy and reverberant environments
K Reindl, Y Zheng, A Schwarz, S Meier, R Maas, A Sehr, W Kellermann
Computer Speech & Language 27 (3), 726-745, 2013
382013
Anchored speech detection and speech recognition
SHK Parthasarathi, B Hoffmeister, B King, R Maas
US Patent App. 15/196,228, 2017
302017
Towards a better understanding of the effect of reverberation on speech recognition performance
A Sehr, EAP Habets, R Maas, W Kellermann
Proc. IWAENC, 2010
262010
Spatial diffuseness features for DNN-based speech recognition in noisy and reverberant environments
A Schwarz, C Huemmer, R Maas, W Kellermann
2015 IEEE International Conference on Acoustics, Speech and Signal†…, 2015
252015
On the application of reverberation suppression to robust speech recognition
R Maas, EAP Habets, A Sehr, W Kellermann
2012 IEEE International Conference on Acoustics, Speech and Signal†…, 2012
222012
A two-channel acoustic front-end for robust automatic speech recognition in noisy and reverberant environments
R Maas, A Schwarz, Y Zheng, K Reindl, S Meier, A Sehr, W Kellermann
Machine Listening in Multisource Environments, 2011
212011
The elitist particle filter based on evolutionary strategies as novel approach for nonlinear acoustic echo cancellation
C Huemmer, C Hofmann, R Maas, A Schwarz, W Kellermann
2014 IEEE International Conference on Acoustics, Speech and Signal†…, 2014
192014
Uncertainty decoding for DNN-HMM hybrid systems based on numerical sampling
C Huemmer, R Maas, A Schwarz, RF Astudillo, W Kellermann
Sixteenth Annual Conference of the International Speech Communication†…, 2015
142015
The significance-aware EPFES to estimate a memoryless preprocessor for nonlinear acoustic echo cancellation
C Huemmer, C Hofmann, R Maas, W Kellermann
2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP†…, 2014
142014
Robust Speech Recognition via Anchor Word Representations.
B King, IF Chen, Y Vaizman, Y Liu, R Maas, SHK Parthasarathi, ...
INTERSPEECH, 2471-2475, 2017
132017
The NLMS algorithm with time-variant optimum stepsize derived from a Bayesian network perspective
C Huemmer, R Maas, W Kellermann
IEEE Signal Processing Letters 22 (11), 1874-1878, 2015
122015
Frame-wise HMM adaptation using state-dependent reverberation estimates
A Sehr, R Maas, W Kellermann
2011 IEEE International Conference on Acoustics, Speech and Signal†…, 2011
122011
Anchored Speech Detection.
R Maas, SHK Parthasarathi, B King, R Huang, B Hoffmeister
INTERSPEECH 16, 2963-2967, 2016
112016
A novel approach for matched reverberant training of HMMs using data pairs
A Sehr, C Hofmann, R Maas, W Kellermann
Eleventh Annual Conference of the International Speech Communication Association, 2010
112010
A new uncertainty decoding scheme for DNN-HMM hybrid systems with multichannel speech enhancement
C Huemmer, A Schwarz, R Maas, H Barfuss, RF Astudillo, W Kellermann
2016 IEEE International Conference on Acoustics, Speech and Signal†…, 2016
92016
On Bayesian networks in speech signal processing
R Maas, C Huemmer, C Hofmann, W Kellermann
Speech Communication; 11. ITG Symposium, 1-4, 2014
92014
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