1 citations · 1 across the 7 of their papers we have counts for
7 papers
Gradient-free Post-hoc Explainability Using Distillation Aided Learnable Approach
Debarpan Bhattacharya, Amir H. Poorjam, Deepak Mittal +1
The recent advancements in artificial intelligence (AI), with the release of several large models having only query access, make a strong case for explainability of deep models in…
Interpretable Acoustic Representation Learning on Breathing and Speech Signals for COVID-19 Detection
Debottam Dutta, Debarpan Bhattacharya, Sriram Ganapathy +3
In this paper, we describe an approach for representation learning of audio signals for the task of COVID-19 detection. The raw audio samples are processed with a bank of 1-D convo…
Svadhyaya system for the Second Diagnosing COVID-19 using Acoustics Challenge 2021
Deepak Mittal, Amir H. Poorjam, Debottam Dutta +4
This report describes the system used for detecting COVID-19 positives using three different acoustic modalities, namely speech, breathing, and cough in the second DiCOVA challenge…
SpliceOut: A Simple and Efficient Audio Augmentation Method
Arjit Jain, Pranay Reddy Samala, Deepak Mittal +2
Time masking has become a de facto augmentation technique for speech and audio tasks, including automatic speech recognition (ASR) and audio classification, most notably as a part…
ProAlignNet : Unsupervised Learning for Progressively Aligning Noisy Contours
VSR Veeravasarapu, Abhishek Goel, Deepak Mittal +1
Contour shape alignment is a fundamental but challenging problem in computer vision, especially when the observations are partial, noisy, and largely misaligned. Recent ConvNet-bas…
Studying the Plasticity in Deep Convolutional Neural Networks using Random Pruning
Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra +1
Recently there has been a lot of work on pruning filters from deep convolutional neural networks (CNNs) with the intention of reducing computations.The key idea is to rank the filt…
Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks
Deepak Mittal, Shweta Bhardwaj, Mitesh M. Khapra +1
Recently there has been a lot of work on pruning filters from deep convolutional neural networks (CNNs) with the intention of reducing computations. The key idea is to rank the fil…