Exploring automatic diagnosis of COVID-19 from crowdsourced respiratory sound data
Audio signals generated by the human body (eg, sighs, breathing, heart, digestion, vibration
sounds) have routinely been used by clinicians as indicators to diagnose disease or assess …
sounds) have routinely been used by clinicians as indicators to diagnose disease or assess …
End-to-end convolutional neural network enables COVID-19 detection from breath and cough audio: a pilot study
Background Since the emergence of COVID-19 in December 2019, multidisciplinary
research teams have wrestled with how best to control the pandemic in light of its …
research teams have wrestled with how best to control the pandemic in light of its …
COVID-19 detection in cough, breath and speech using deep transfer learning and bottleneck features
We present an experimental investigation into the effectiveness of transfer learning and
bottleneck feature extraction in detecting COVID-19 from audio recordings of cough, breath …
bottleneck feature extraction in detecting COVID-19 from audio recordings of cough, breath …
Funaudiollm: Voice understanding and generation foundation models for natural interaction between humans and llms
This report introduces FunAudioLLM, a model family designed to enhance natural voice
interactions between humans and large language models (LLMs). At its core are two …
interactions between humans and large language models (LLMs). At its core are two …
Pay attention to the cough: Early diagnosis of COVID-19 using interpretable symptoms embeddings with cough sound signal processing
A Pal, M Sankarasubbu - Proceedings of the 36th Annual ACM …, 2021 - dl.acm.org
COVID-19 (coronavirus disease 2019) pandemic caused by SARS-CoV-2 has led to a
treacherous and devastating catastrophe for humanity. No specific antivirus drugs or …
treacherous and devastating catastrophe for humanity. No specific antivirus drugs or …
Virufy: A multi-branch deep learning network for automated detection of COVID-19
Fast and affordable solutions for COVID-19 testing are necessary to contain the spread of
the global pandemic and help relieve the burden on medical facilities. Currently, limited …
the global pandemic and help relieve the burden on medical facilities. Currently, limited …
[HTML][HTML] High accuracy classification of COVID-19 coughs using Mel-frequency cepstral coefficients and a Convolutional Neural Network with a use case for smart …
Diagnosing COVID-19 early in domestic settings is possible through smart home devices
that can classify audio input of coughs, and determine whether they are COVID-19 …
that can classify audio input of coughs, and determine whether they are COVID-19 …
Hierarchical multi-modal transformer for automatic detection of COVID-19
Automated COVID-19 detection based on analysis of cough recordings has been an
important field of study, as efficient and accurate methods are necessary to contain the …
important field of study, as efficient and accurate methods are necessary to contain the …
COVID-19 detection with a novel multi-type deep fusion method using breathing and coughing information
S Liu, A Mallol-Ragolta… - 2021 43rd Annual …, 2021 - ieeexplore.ieee.org
This study explores the use of deep learning-based methods for the automatic detection of
COVID-19. Specifically, we aim to investigate the involvement of the virus in the respiratory …
COVID-19. Specifically, we aim to investigate the involvement of the virus in the respiratory …
Covid-19 detection using audio spectral features and machine learning
In this research and education REU project, we use audio waveform signatures of coughing
to determine whether COVID-19 can be diagnosed. More specifically, we determine …
to determine whether COVID-19 can be diagnosed. More specifically, we determine …