Deepak Baby
Title
Cited by
Cited by
Year
Sergan: Speech enhancement using relativistic generative adversarial networks with gradient penalty
D Baby, S Verhulst
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
442019
Coupled dictionaries for exemplar-based speech enhancement and automatic speech recognition
D Baby, T Virtanen, JF Gemmeke
IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (11 …, 2015
252015
Exemplar-based speech enhancement for deep neural network based automatic speech recognition
D Baby, J Gemmeke, T Virtanen, H Van hamme
IEEE ICASSP 2015, 2015
212015
Coupled dictionary training for exemplar-based speech enhancement
D Baby, T Virtanen, T Barker, H Van hamme
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International …, 2014
182014
Ordered Orthogonal Matching Pursuit
D Baby, SRB Pillai
Communications (NCC), 2012 National Conference on, 2012
10*2012
Biophysically-inspired features improve the generalizability of neural network-based speech enhancement systems
D Baby, S Verhulst
INTERSPEECH, 2018
92018
Joint Denoising and Dereverberation Using Exemplar-Based Sparse Representations and Decaying Norm Constraint
D Baby, H Van hamme
IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (10 …, 2017
92017
Supervised speech dereverberation in noisy environments using exemplar-based sparse representations
D Baby, H Van hamme
Accoustics, Speech and Signal Processing, 2016 IEEE International Conference on, 2016
92016
Real-time audio processing on a Raspberry Pi using deep neural networks
F Drakopoulos, D Baby, S Verhulst
23rd International Congress on Acoustics (ICA 2019), 2827-2834, 2019
52019
Investigating modulation spectrogram features for deep neural network-based automatic speech recognition
D Baby, H Van hamme
Proceedings Interspeech 2015, 2479-2483, 2015
52015
A convolutional neural-network model of human cochlear mechanics and filter tuning for real-time applications
D Baby, A Van Den Broucke, S Verhulst
Nature Machine Intelligence 3 (2), 134-143, 2021
42021
isegan: Improved speech enhancement generative adversarial networks
D Baby
arXiv preprint arXiv:2002.08796, 2020
42020
Exemplar-based noise robust automatic speech recognition using modulation spectrogram features
D Baby, T Virtanen, J Gemmeke, T Barker, H Van hamme
Proceedings SLT 2014, 1-6, 2014
42014
Machines hear better when they have ears
D Baby, S Verhulst
arXiv preprint arXiv:1806.01145, 2018
32018
Coupled dictionary-based speech enhancement for CHiME-3 challenge
D Baby, T Virtanen, H Van hamme
32015
Hearing-Impaired Bio-Inspired Cochlear Models for Real-Time Auditory Applications
A Van Den Broucke, D Baby, S Verhulst
Proc Interspeech 2020, 2842-2846, 2020
22020
Non-negative sparse representations for speech enhancement and recognition
D Baby
22016
Noise robust exemplar matching for speech enhancement: Applications to automatic speech recognition
E Yilmaz, D Baby, H Van hamme
Proceedings Interspeech 2015, 688-692, 2015
22015
Noise robust exemplar matching with coupled dictionaries for single-channel speech enhancement
E Yilmaz, D Baby, H Van hamme
Signal Processing Conference (EUSIPCO), 2015 23rd European, 874-878, 2015
12015
Applying biophysical auditory periphery models for real-time applications and studies of hearing impairment
A Van Den Broucke, F Drakopoulos, D Baby, S Verhulst
e-Forum Acusticum 2020, 3005-3006, 2020
2020
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