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20192021
most citedDeep Learning Based Dereverberation of Temporal Envelopesfor Robust Speech Recognition

3 citations · 6 across the 6 of their papers we have counts for

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eess.AS2021

Dereverberation of Autoregressive Envelopes for Far-field Speech Recognition

Anurenjan Purushothaman, Anirudh Sreeram, Rohit Kumar +1

The task of speech recognition in far-field environments is adversely affected by the reverberant artifacts that elicit as the temporal smearing of the sub-band envelopes. In this…

eess.AS2021

SRIB-LEAP submission to Far-field Multi-Channel Speech Enhancement Challenge for Video Conferencing

R G Prithvi Raj, Rohit Kumar, M K Jayesh +3

This paper presents the details of the SRIB-LEAP submission to the ConferencingSpeech challenge 2021. The challenge involved the task of multi-channel speech enhancement to improve…

eess.AS2021

Towards sound based testing of COVID-19 -- Summary of the first Diagnostics of COVID-19 using Acoustics (DiCOVA) Challenge

Neeraj Kumar Sharma, Ananya Muguli, Prashant Krishnan +3

The technology development for point-of-care tests (POCTs) targeting respiratory diseases has witnessed a growing demand in the recent past. Investigating the presence of acoustic…

eess.AS20213 cited

Multi-modal Point-of-Care Diagnostics for COVID-19 Based On Acoustics and Symptoms

Srikanth Raj Chetupalli, Prashant Krishnan, Neeraj Sharma +6

The research direction of identifying acoustic bio-markers of respiratory diseases has received renewed interest following the onset of COVID-19 pandemic. In this paper, we design…

eess.AS2021

DiCOVA Challenge: Dataset, task, and baseline system for COVID-19 diagnosis using acoustics

Ananya Muguli, Lancelot Pinto, Nirmala R. +9

The DiCOVA challenge aims at accelerating research in diagnosing COVID-19 using acoustics (DiCOVA), a topic at the intersection of speech and audio processing, respiratory health d…

eess.AS20203 cited

Deep Learning Based Dereverberation of Temporal Envelopesfor Robust Speech Recognition

Anurenjan Purushothaman, Anirudh Sreeram, Rohit Kumar +1

Automatic speech recognition in reverberant conditions is a challenging task as the long-term envelopes of the reverberant speech are temporally smeared. In this paper, we propose…