Detection of COVID-19 from speech signal using bio-inspired based cepstral features
Published 2021 View Full Article
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Title
Detection of COVID-19 from speech signal using bio-inspired based cepstral features
Authors
Keywords
Bio-inspired computing, COVID19, Speech signal
Journal
PATTERN RECOGNITION
Volume 117, Issue -, Pages 107999
Publisher
Elsevier BV
Online
2021-04-24
DOI
10.1016/j.patcog.2021.107999
References
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Related references
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- (2020) Biswajit Karan et al. Biomedical Signal Processing and Control
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- (2019) Biswajit Karan et al. Biocybernetics and Biomedical Engineering
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- (2019) Divyaansh Devarriya et al. EXPERT SYSTEMS WITH APPLICATIONS
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- Spectral-domain speech enhancement for speech recognition
- (2017) Chang Huai YOU et al. SPEECH COMMUNICATION
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- (2016) Jake Lever et al. NATURE METHODS
- Auditory Model-Based Design and Optimization of Feature Vectors for Automatic Speech Recognition
- (2010) Saikat Chatterjee et al. IEEE Transactions on Audio Speech and Language Processing
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- (2009) Haibo He et al. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
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