Hybrid CNN-LSTM Speaker Identification Framework for Evaluating the Impact of Face Masks
Author:
Affiliation:
1. University of Sharjah,Department of Electrical Eng,Sharjah,United Arab Emirates
2. Khalifa University,Department of EECS,Abu Dhabi,United Arab Emirates
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9989539/9990040/09990138.pdf?arnumber=9990138
Reference21 articles.
1. Paralinguistic Classification of Mask Wearing by Image Classifiers and Fusion
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4. Learning Higher Representations from pre-trained Deep Models with Data Augmentation for the C OM P AR E 2020 Challenge Mask Task Chair of Embedded Intelligence for Health Care and Wellbeing, University of Augsburg, Germany;koike,2020
5. COVID-19 Detection Systems Using Deep-Learning Algorithms Based on Speech and Image Data
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1. Densely Connected Networks with Multiple Features for Classifying Sound Signals with Reverberation;Sensors;2023-08-17
2. Unsupervised Arabic Speech Embedding Model for Speaker Identification;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18
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