no code implementations • 11 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.
no code implementations • 16 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.
1 code implementation • 2 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.
no code implementations • 22 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.