Shrikant Venkataramani
Shrikant Venkataramani
Applied Scientist, Amazon Web Services
Verified email at amazon.com
Title
Cited by
Cited by
Year
End-to-end source separation with adaptive front-ends
S Venkataramani, J Casebeer, P Smaragdis
Asilomar, 2018
512018
A neural network alternative to non-negative audio models
P Smaragdis, S Venkataramani
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
502017
Adaptive front-ends for end-to-end source separation
S Venkataramani, J Casebeer, P Smaragdis
Proc. NIPS, 2017
342017
Unsupervised deep clustering for source separation: Direct learning from mixtures using spatial information
E Tzinis, S Venkataramani, P Smaragdis
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
262019
Class-conditional embeddings for music source separation
P Seetharaman, G Wichern, S Venkataramani, J Le Roux
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
202019
Two-step sound source separation: Training on learned latent targets
E Tzinis, S Venkataramani, Z Wang, C Subakan, P Smaragdis
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
172020
Performance Based Cost Functions for End-to-End Speech Separation
S Venkataramani, R Higa, P Smaragdis
Asia-Pacific Signal and Information Processing Association Annual Summit and …, 2018
162018
Neural network alternatives to convolutive audio models for source separation
S Venkataramani, C Subakan, P Smaragdis
2017 IEEE 27th International Workshop on Machine Learning for Signal …, 2017
122017
End-to-end networks for supervised single-channel speech separation
S Venkataramani, P Smaragdis
arXiv preprint arXiv:1810.02568, 2018
92018
Vocal Separation using Singer-Vowel Priors Obtained from Polyphonic Audio.
S Venkataramani, N Nayak, P Rao, R Velmurugan
ISMIR, 283-288, 2014
42014
Self-supervised Learning for Speech Enhancement
YC Wang, S Venkataramani, P Smaragdis
arXiv preprint arXiv:2006.10388, 2020
32020
End-to-end non-negative autoencoders for sound source separation
S Venkataramani, E Tzinis, P Smaragdis
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
32020
A style transfer approach to source separation
S Venkataramani, E Tzinis, P Smaragdis
2019 IEEE Workshop on Applications of Signal Processing to Audio and …, 2019
22019
Efficient Trainable Front-Ends for Neural Speech Enhancement
J Casebeer, U Isik, S Venkataramani, A Krishnaswamy
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
12020
Personalized PercepNet: Real-time, Low-complexity Target Voice Separation and Enhancement
R Giri, S Venkataramani, JM Valin, U Isik, A Krishnaswamy
arXiv preprint arXiv:2106.04129, 2021
2021
End-to-end non-negative auto-encoders: a deep neural alternative to non-negative audio modeling
S Venkataramani
University of Illinois at Urbana-Champaign, 2020
2020
Two-Step Sound Source Separation: Training on Learned Latent Targets (Presentation)
E Tzinis, S Venkataramani, Z Wang, C Subakan, P Smaragdis
2020
Automatic voiceover correction system
S Venkataramani, P Smaragdis, G Mysore
US Patent 10,453,475, 2019
2019
Unsuper vised Deep Clustering for Source Separation: Direct Learning from Mixtures Using Spatial Information Slides
E Tzinis, S Venkataramani, P Smaragdis
2019
AutoDub: Automatic Redubbing for Voiceover Editing
S Venkataramani, P Smaragdis, G Mysore
Proceedings of the 30th Annual ACM Symposium on User Interface Software and …, 2017
2017
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