43 citations · 45 across the 5 of their papers we have counts for
5 papers
AugCodec: A Low-Bitrate Disentangled Neural Speech Codec via Data Augmentation
Dongmei Wang, Xiaohang Sun, Yang Liu +10
We propose AugCodec, a low-bitrate disentangled neural speech codec that leverages data augmentation to decompose speech into three distinct components: semantic, speaker, and pros…
BEATs: Audio Pre-Training with Acoustic Tokenizers
Sanyuan Chen, Yu Wu, Chengyi Wang +4
The massive growth of self-supervised learning (SSL) has been witnessed in language, vision, speech, and audio domains over the past few years. While discrete label prediction is w…
Maximizing Audio Event Detection Model Performance on Small Datasets Through Knowledge Transfer, Data Augmentation, And Pretraining: An Ablation Study
Daniel Tompkins, Kshitiz Kumar, Jian Wu
An Xception model reaches state-of-the-art (SOTA) accuracy on the ESC-50 dataset for audio event detection through knowledge transfer from ImageNet weights, pretraining on AudioSet…
COVID-19 Detection Using Recorded Coughs in the 2021 DiCOVA Challenge
Benjamin Elizalde, Daniel Tompkins
COVID-19 has resulted in over 100 million infections and caused worldwide lock downs due to its high transmission rate and limited testing options. Current diagnostic tests can be…
Multi-label Sound Event Retrieval Using a Deep Learning-based Siamese Structure with a Pairwise Presence Matrix
Jianyu Fan, Eric Nichols, Daniel Tompkins +3
Realistic recordings of soundscapes often have multiple sound events co-occurring, such as car horns, engine and human voices. Sound event retrieval is a type of content-based sear…