83 citations · 114 across the 10 of their papers we have counts for
10 papers
Towards Selection of Text-to-speech Data to Augment ASR Training
Shuo Liu, Leda Sarı, Chunyang Wu +4
This paper presents a method for selecting appropriate synthetic speech samples from a given large text-to-speech (TTS) dataset as supplementary training data for an automatic spee…
HEAR4Health: A blueprint for making computer audition a staple of modern healthcare
Andreas Triantafyllopoulos, Alexander Kathan, Alice Baird +20
Recent years have seen a rapid increase in digital medicine research in an attempt to transform traditional healthcare systems to their modern, intelligent, and versatile equivalen…
An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Era
Andreas Triantafyllopoulos, Björn W. Schuller, Gökçe İymen +9
Speech is the fundamental mode of human communication, and its synthesis has long been a core priority in human-computer interaction research. In recent years, machines have manage…
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…
Multistage linguistic conditioning of convolutional layers for speech emotion recognition
Andreas Triantafyllopoulos, Uwe Reichel, Shuo Liu +3
In this contribution, we investigate the effectiveness of deep fusion of text and audio features for categorical and dimensional speech emotion recognition (SER). We propose a nove…
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…