Zobrazeno 1 - 10
of 114
pro vyhledávání: '"Sivaraman, Ganesh"'
When it comes to authentication in speaker verification systems, not all utterances are created equal. It is essential to estimate the quality of test utterances in order to account for varying acoustic conditions. In addition to the net-speech durat
Externí odkaz:
http://arxiv.org/abs/2407.08017
Autor:
Sivaraman, Ganesh, Benmore, Chris J.
Bridging the gap between diffuse x-ray or neutron scattering measurements and predicted structures derived from atom-atom pair potentials in disordered materials, has been a longstanding challenge in condensed matter physics. This perspective gives a
Externí odkaz:
http://arxiv.org/abs/2403.00259
Autor:
Ward, Logan, Pauloski, J. Gregory, Hayot-Sasson, Valerie, Chard, Ryan, Babuji, Yadu, Sivaraman, Ganesh, Choudhury, Sutanay, Chard, Kyle, Thakur, Rajeev, Foster, Ian
Applications that fuse machine learning and simulation can benefit from the use of multiple computing resources, with, for example, simulation codes running on highly parallel supercomputers and AI training and inference tasks on specialized accelera
Externí odkaz:
http://arxiv.org/abs/2303.08803
Autor:
Benmore, Chris J., Sivaraman, Ganesh
Publikováno v:
Journal of Chemical Physics; 10/21/2024, Vol. 161 Issue 15, p1-7, 7p
Publikováno v:
Proc. Interspeech 2022
Multi-task learning (MTL) frameworks have proven to be effective in diverse speech related tasks like automatic speech recognition (ASR) and speech emotion recognition. This paper proposes a MTL framework to perform acoustic-to-articulatory speech in
Externí odkaz:
http://arxiv.org/abs/2205.13755
Audio Data Augmentation for Acoustic-to-articulatory Speech Inversion using Bidirectional Gated RNNs
Data augmentation has proven to be a promising prospect in improving the performance of deep learning models by adding variability to training data. In previous work with developing a noise robust acoustic-to-articulatory speech inversion system, we
Externí odkaz:
http://arxiv.org/abs/2205.13086
Multi-resolution spectro-temporal features of a speech signal represent how the brain perceives sounds by tuning cortical cells to different spectral and temporal modulations. These features produce a higher dimensional representation of the speech s
Externí odkaz:
http://arxiv.org/abs/2203.05780
Autor:
Ward, Logan, Sivaraman, Ganesh, Pauloski, J. Gregory, Babuji, Yadu, Chard, Ryan, Dandu, Naveen, Redfern, Paul C., Assary, Rajeev S., Chard, Kyle, Curtiss, Larry A., Thakur, Rajeev, Foster, Ian
Scientific applications that involve simulation ensembles can be accelerated greatly by using experiment design methods to select the best simulations to perform. Methods that use machine learning (ML) to create proxy models of simulations show parti
Externí odkaz:
http://arxiv.org/abs/2110.02827
Autor:
Hickey, Kevin, Feinstein, Jeremy, Sivaraman, Ganesh, MacDonell, Margaret, Yan, Eugene, Matherson, Carlos, Coia, Scott, Xu, Jason, Picel, Kurt
Publikováno v:
In Computational Materials Science April 2024 238
Publikováno v:
Published at ICLR 2021 Workshop on Machine Learning for Preventing and Combating Pandemics
We examine a pair of graph generative models for the therapeutic design of novel drug candidates targeting SARS-CoV-2 viral proteins. Due to a sense of urgency, we chose well-validated models with unique strengths: an autoencoder that generates molec
Externí odkaz:
http://arxiv.org/abs/2105.10489