409 citations · 1.5k across the 95 of their papers we have counts for
3 papers · 2 filters
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…
Approach to Learning Generalized Audio Representation Through Batch Embedding Covariance Regularization and Constant-Q Transforms
Ankit Shah, Shuyi Chen, Kejun Zhou +2
General-purpose embedding is highly desirable for few-shot even zero-shot learning in many application scenarios, including audio tasks. In order to understand representations bett…
PAAPLoss: A Phonetic-Aligned Acoustic Parameter Loss for Speech Enhancement
Muqiao Yang, Joseph Konan, David Bick +5
Despite rapid advancement in recent years, current speech enhancement models often produce speech that differs in perceptual quality from real clean speech. We propose a learning o…