4 citations · 10 across the 5 of their papers we have counts for
6 papers
A Temporal-oriented Broadcast ResNet for COVID-19 Detection
Xin Jing, Shuo Liu, Emilia Parada-Cabaleiro +4
Detecting COVID-19 from audio signals, such as breathing and coughing, can be used as a fast and efficient pre-testing method to reduce the virus transmission. Due to the promising…
Audio Self-supervised Learning: A Survey
Shuo Liu, Adria Mallol-Ragolta, Emilia Parada-Cabeleiro +5
Inspired by the humans' cognitive ability to generalise knowledge and skills, Self-Supervised Learning (SSL) targets at discovering general representations from large-scale data wi…
Fitbeat: COVID-19 Estimation based on Wristband Heart Rate
Shuo Liu, Jing Han, Estela Laporta Puyal +26
This study investigates the potential of deep learning methods to identify individuals with suspected COVID-19 infection using remotely collected heart-rate data. The study utilise…
N-HANS: Introducing the Augsburg Neuro-Holistic Audio-eNhancement System
Shuo Liu, Gil Keren, Björn Schuller
N-HANS is a Python toolkit for in-the-wild audio enhancement, including speech, music, and general audio denoising, separation, and selective noise or source suppression. The funct…
AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition
Fabien Ringeval, Björn Schuller, Michel Valstar +14
The Audio/Visual Emotion Challenge and Workshop (AVEC 2019) "State-of-Mind, Detecting Depression with AI, and Cross-cultural Affect Recognition" is the ninth competition event aime…
Single-Channel Speech Separation with Auxiliary Speaker Embeddings
Shuo Liu, Gil Keren, Björn Schuller
We present a novel source separation model to decompose asingle-channel speech signal into two speech segments belonging to two different speakers. The proposed model is a neural n…