Automatic Diagnosis of Snoring Sounds with the Developed Artificial Intelligence-based Hybrid Model
نویسندگان
چکیده
Sleep patterns and sleep continuity have a great impact on people's quality of life. The sound snoring both reduces the snorer disturbs other people in environment. Interpretation signals by experts diagnosis disease is difficult costly process. Therefore, study, an artificial intelligence-based hybrid model was developed for classification sounds. In proposed method, first all, were converted into images using Mel-spectrogram method. feature maps obtained Alexnet Resnet101 architectures. After combining that are different each architecture, dimension reduction made NCA map optimized method classified Bilayered Neural Network. addition, spectrogram with 8 CNN models to compare performance model. Later, order test model, MFCC classifiers. accuracy value 99.5%.
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ژورنال
عنوان ژورنال: F?rat University Turkish journal of science & technology
سال: 2022
ISSN: ['1308-9080', '1308-9099']
DOI: https://doi.org/10.55525/tjst.1127124