11 citations · 26 across the 7 of their papers we have counts for
7 papers
Using voice analysis as an early indicator of risk for depression in young adults
Klaus R. Scherer, Felix Burkhardt, Uwe D. Reichel +2
Increasingly frequent publications in the literature report voice quality differences between depressed patients and controls. Here, we examine the possibility of using voice analy…
Does the Definition of Difficulty Matter? Scoring Functions and their Role for Curriculum Learning
Simon Rampp, Manuel Milling, Andreas Triantafyllopoulos +1
Curriculum learning (CL) describes a machine learning training strategy in which samples are gradually introduced into the training process based on their difficulty. Despite a par…
Sparks of Large Audio Models: A Survey and Outlook
Siddique Latif, Moazzam Shoukat, Fahad Shamshad +8
This survey paper provides a comprehensive overview of the recent advancements and challenges in applying large language models to the field of audio signal processing. Audio proce…
MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning
Zheng Lian, Haiyang Sun, Licai Sun +15
The first Multimodal Emotion Recognition Challenge (MER 2023) was successfully held at ACM Multimedia. The challenge focuses on system robustness and consists of three distinct tra…
Proceedings of the ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts
Alice Baird, Panagiotis Tzirakis, Gauthier Gidel +7
This is the Proceedings of the ICML Expressive Vocalization (ExVo) Competition. The ExVo competition focuses on understanding and generating vocal bursts: laughs, gasps, cries, and…
Remote smartphone-based speech collection: acceptance and barriers in individuals with major depressive disorder
Judith Dineley, Grace Lavelle, Daniel Leightley +22
The ease of in-the-wild speech recording using smartphones has sparked considerable interest in the combined application of speech, remote measurement technology (RMT) and advanced…
Guided Generative Adversarial Neural Network for Representation Learning and High Fidelity Audio Generation using Fewer Labelled Audio Data
Kazi Nazmul Haque, Rajib Rana, John H. L. Hansen +1
Recent improvements in Generative Adversarial Neural Networks (GANs) have shown their ability to generate higher quality samples as well as to learn good representations for transf…