3 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.SD2023★ 1 cited
Improving Perceptual Quality, Intelligibility, and Acoustics on VoIP Platforms
Joseph Konan, Ojas Bhargave, Shikhar Agnihotri +12
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 (V…
cs.SD2023★ 1 cited
Speech Enhancement for Virtual Meetings on Cellular Networks
Hojeong Lee, Minseon Gwak, Kawon Lee +3
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 spee…
cs.CL2020★ 3 cited
ST-BERT: Cross-modal Language Model Pre-training For End-to-end Spoken Language Understanding
Minjeong Kim, Gyuwan Kim, Sang-Woo Lee +1
Language model pre-training has shown promising results in various downstream tasks. In this context, we introduce a cross-modal pre-trained language model, called Speech-Text BERT…