6 citations · 13 across the 14 of their papers we have counts for
14 papers
TILT: Model-Intrinsic Reward Alignment For Compositional Diffusion
Debottam Dutta, Jaehoon Hahm, Jianchong Chen +1
Consider conditional generation where is a prompt composed of multiple concepts . Diffusion models often struggle with compositional…
Personalized Image Generation via Human-in-the-loop Bayesian Optimization
Rajalaxmi Rajagopalan, Debottam Dutta, Yu-Lin Wei +1
Imagine Alice has a specific image in her mind, say, the view of the street in which she grew up during her childhood. To generate that exact image, she guides a generativ…
Learning Energy-based Variational Latent Prior for VAEs
Debottam Dutta, Chaitanya Amballa, Zhongweiyang Xu +2
Variational Auto-Encoders (VAEs) are known to generate blurry and inconsistent samples. One reason for this is the "prior hole" problem. A prior hole refers to regions that have hi…
Steer Away From Mode Collisions: Improving Composition In Diffusion Models
Debottam Dutta, Jianchong Chen, Rajalaxmi Rajagopalan +2
We propose to improve multi-concept prompt fidelity in text-to-image diffusion models. We begin with common failure cases - prompts like "a cat and a dog" that sometimes yields ima…
Estimating Multi-chirp Parameters using Curvature-guided Langevin Monte Carlo
Sattwik Basu, Debottam Dutta, Yu-Lin Wei +1
This paper considers the problem of estimating chirp parameters from a noisy mixture of chirps. While a rich body of work exists in this area, challenges remain when extending thes…
Multi-Source Music Generation with Latent Diffusion
Zhongweiyang Xu, Debottam Dutta, Yu-Lin Wei +1
Most music generation models directly generate a single music mixture. To allow for more flexible and controllable generation, the Multi-Source Diffusion Model (MSDM) has been prop…
Speech enhancement with frequency domain auto-regressive modeling
Anurenjan Purushothaman, Debottam Dutta, Rohit Kumar +1
Speech applications in far-field real world settings often deal with signals that are corrupted by reverberation. The task of dereverberation constitutes an important step to impro…
Coswara: A respiratory sounds and symptoms dataset for remote screening of SARS-CoV-2 infection
Debarpan Bhattacharya, Neeraj Kumar Sharma, Debottam Dutta +8
This paper presents the Coswara dataset, a dataset containing diverse set of respiratory sounds and rich meta-data, recorded between April-2020 and February-2022 from 2635 individu…
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…
Analyzing the impact of SARS-CoV-2 variants on respiratory sound signals
Debarpan Bhattacharya, Debottam Dutta, Neeraj Kumar Sharma +8
The COVID-19 outbreak resulted in multiple waves of infections that have been associated with different SARS-CoV-2 variants. Studies have reported differential impact of the varian…
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…
Coswara: A website application enabling COVID-19 screening by analysing respiratory sound samples and health symptoms
Debarpan Bhattacharya, Debottam Dutta, Neeraj Kumar Sharma +8
The COVID-19 pandemic has accelerated research on design of alternative, quick and effective COVID-19 diagnosis approaches. In this paper, we describe the Coswara tool, a website a…
The Second DiCOVA Challenge: Dataset and performance analysis for COVID-19 diagnosis using acoustics
Neeraj Kumar Sharma, Srikanth Raj Chetupalli, Debarpan Bhattacharya +3
The Second Diagnosis of COVID-19 using Acoustics (DiCOVA) Challenge aimed at accelerating the research in acoustics based detection of COVID-19, a topic at the intersection of acou…
A Multi-Head Relevance Weighting Framework For Learning Raw Waveform Audio Representations
Debottam Dutta, Purvi Agrawal, Sriram Ganapathy
In this work, we propose a multi-head relevance weighting framework to learn audio representations from raw waveforms. The audio waveform, split into windows of short duration, are…