Toggle navigation
BIP!
Services
Finder
Readings
Scholar
Data, API & Code
Indicators
About
Help
Log In
Clear all
2021 •
Investigating feature selection and explainability for COVID-19 diagnostics from cough sounds
Authors:
Avila Flavio, Amir Hossein Poorjam, Deepak Mittal, Charles Dognin, Ananya Muguli, Rohit Kumar, Srikanth Raj Chetupalli, Sriram Ganapathy, Maneesh Singh
Abstract:
In this paper, we propose an approach to automatically classify COVID-19 and non-COVID-19 cough samples based on the combination of both feature engineering and deep learning models. In the feature engineering approach, we develop a support vector machine classifier over high dimensional (6373D) space of acoustic features. In the deep learning-based approach, on the other hand, we apply a convolutional neural network trained on the log-mel spectrograms. These two methodologically diverse models are then combined by fusing the probability scores (...)
In this paper, we propose an approach to automatically classify COVID-19 and non-COVID-19 cough samples based on the combination of both feature engineering and deep learning models. In the feature engineering approach, we develop a support vector machine classifier over high dimensional (6373D) space of acoustic features. In the deep learning-based approach, on the other hand, we apply a convolutional neural network trained on the log-mel spectrograms. These two methodologically diverse models are then combined by fusing the probability scores of the models. The proposed system, which ranked 9th on the 2021 Diagnosing COVID-19 using Acoustics (Di- COVA) challenge leaderboard, obtained an area under the receiver operating characteristic curve (AUC) of 0:81 on the blind test data set, which is a 10:9% absolute improvement compared to the baseline. Moreover, we analyze the explainability of the deep learning-based model when detecting COVID-19 from cough signals. Copyright © 2021 ISCA.
(Read More)
External links:
OpenAIRE
Works in BIP! associated with the specified OpenAIRE research product
Investigating Feature Selection and Explainability for COVID-19 Diagnostics from Cough Sou (...)
Flavio Avila, Amir H. Poorjam, Deepak Mittal, Charles Dognin, Ananya Muguli, Rohit Kumar, Srikanth R (...)
Interspeech 2021
·
2021
Artificial intelligence
|
Machine learning
|
Speech recognition
|
We have placed cookies on your device to help make this website and the services we offer better. By using this site, you agree to the use of cookies.
Learn more
I accept
Are you sure you want to delete this bookmark ?