[PDF][PDF] Investigating biases in COVID-19 diagnostic systems processed with automated speech anonymization algorithms
Y Zhu, M Imoussaïne-Aïkous… - 3rd Symposium on …, 2023 - isca-archive.org
Automated voice anonymization algorithms are used to obfuscate speaker identity while
leaving other vocal attributes untouched; they have been used for eg, speech recognition …
leaving other vocal attributes untouched; they have been used for eg, speech recognition …
TinyM2Net-V2: A Compact Low-power Software Hardware Architecture for Multimodal Deep Neural Networks
With the evaluation of Artificial Intelligence (AI), there has been a resurgence of interest in
how to use AI algorithms on low-power embedded systems to broaden potential use cases …
how to use AI algorithms on low-power embedded systems to broaden potential use cases …
Dissociating COVID-19 from other respiratory infections based on acoustic, motor coordination, and phonemic patterns
In the face of the global pandemic caused by the disease COVID-19, researchers have
increasingly turned to simple measures to detect and monitor the presence of the disease in …
increasingly turned to simple measures to detect and monitor the presence of the disease in …
Considerations and Challenges for Real-World Deployment of an Acoustic-Based COVID-19 Screening System
Coronavirus disease 2019 (COVID-19) has led to countless deaths and widespread global
disruptions. Acoustic-based artificial intelligence (AI) tools could provide a simple, scalable …
disruptions. Acoustic-based artificial intelligence (AI) tools could provide a simple, scalable …
[HTML][HTML] Spectral–temporal saliency masks and modulation tensorgrams for generalizable COVID-19 detection
Speech COVID-19 detection systems have gained popularity as they represent an easy-to-
use and low-cost solution that is well suited for at-home long-term monitoring of patients with …
use and low-cost solution that is well suited for at-home long-term monitoring of patients with …
TinyMNet-V3: Memory-Aware Compressed Multimodal Deep Neural Networks for Sustainable Edge Deployment
HA Rashid, T Mohsenin - arXiv preprint arXiv:2405.12353, 2024 - arxiv.org
The advancement of sophisticated artificial intelligence (AI) algorithms has led to a notable
increase in energy usage and carbon dioxide emissions, intensifying concerns about …
increase in energy usage and carbon dioxide emissions, intensifying concerns about …
Detection of covid-19 from joint time and frequency analysis of speech, breathing and cough audio
J Harvill, Y Wani, M Chatterjee, M Alam… - ICASSP 2022-2022 …, 2022 - ieeexplore.ieee.org
The distinct cough sounds produced by a variety of respiratory diseases suggest the
potential for the development of a new class of audio bio-markers for the detection of COVID …
potential for the development of a new class of audio bio-markers for the detection of COVID …
Interpretable acoustic representation learning on breathing and speech signals for covid-19 detection
In this paper, we describe an approach for representation learning of audio signals for the
task of COVID-19 detection. The raw audio samples are processed with a bank of 1-D …
task of COVID-19 detection. The raw audio samples are processed with a bank of 1-D …
On the importance of different cough phases for COVID-19 detection
Cough is an important symptom of numerous respiratory diseases, including COVID-19.
While different cough phases (ie, inhalation, compression, and expulsion) have been shown …
While different cough phases (ie, inhalation, compression, and expulsion) have been shown …
Synthesizing Cough Audio with GAN for COVID-19 Detection
Y Saleh - arXiv preprint arXiv:2305.04810, 2023 - arxiv.org
For this final year project, the goal is to add to the published works within data synthesis for
health care. The end product of this project is a trained model that generates synthesized …
health care. The end product of this project is a trained model that generates synthesized …