Search Results for author: Ojas Bhargave

Found 4 papers, 1 papers with code

Psychoacoustic Challenges Of Speech Enhancement On VoIP Platforms

no code implementations11 Oct 2023 Joseph Konan, Ojas Bhargave, Shikhar Agnihotri, Shuo Han, Yunyang Zeng, Ankit Shah, Bhiksha Raj

Within the ambit of VoIP (Voice over Internet Protocol) telecommunications, the complexities introduced by acoustic transformations merit rigorous analysis.

Benchmarking Denoising +1

Improving Perceptual Quality, Intelligibility, and Acoustics on VoIP Platforms

no code implementations16 Mar 2023 Joseph Konan, Ojas Bhargave, Shikhar Agnihotri, Hojeong Lee, Ankit Shah, Shuo Han, Yunyang Zeng, Amanda Shu, Haohui Liu, Xuankai Chang, Hamza Khalid, Minseon Gwak, Kawon Lee, Minjeong Kim, Bhiksha Raj

In this paper, we present a method for fine-tuning models trained on the Deep Noise Suppression (DNS) 2020 Challenge to improve their performance on Voice over Internet Protocol (VoIP) applications.

Multi-Task Learning Speech Enhancement +2

Speech Enhancement for Virtual Meetings on Cellular Networks

1 code implementation2 Feb 2023 Hojeong Lee, Minseon Gwak, Kawon Lee, Minjeong Kim, Joseph Konan, Ojas Bhargave

We study speech enhancement using deep learning (DL) for virtual meetings on cellular devices, where transmitted speech has background noise and transmission loss that affects speech quality.

Speech Enhancement

Cellular Network Speech Enhancement: Removing Background and Transmission Noise

no code implementations22 Jan 2023 Amanda Shu, Hamza Khalid, Haohui Liu, Shikhar Agnihotri, Joseph Konan, Ojas Bhargave

The primary objective of speech enhancement is to reduce background noise while preserving the target's speech.

Speech Enhancement

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