A hybrid CNN and reinforcement learning framework for speaker identification using Mel-Spectrogram and continuous wavelet transform features. [PDF]
Sci RepHeir FM, Najafzadeh H, Erfani S.
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Firearm classification from acoustic signals using combined mel spectrogram, MFCC, LFCC, and CRNN networks. [PDF]
Sci RepElkarous L, Jeridi MH, Dhouibi M.
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Optimized Music Classification with a Hybrid VGG16-RNN Using Mel-Spectrogram and MFCC Features
Music classification using deep neural networks has gained a lot of attention in recent years. This is due to the difficult task of capturing every essential aspect of music in features and interpretability of classifiers.
Ashraf, Mohsin, Ashraf , Saima
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Research on automatic assessment of the severity of unilateral vocal cord paralysis based on Mel-spectrogram and convolutional neural networks. [PDF]
Biomed Eng OnlineMa S +8 more
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Implementing Mel-Spectrogram Analysis for Emotion Recognition in Speech
INTERNATIONAL JOURNAL OF RESEARCH IN SCIENCE AND TECHNOLOGY, 2023 openaire +1 more source
MelTrans: Mel-Spectrogram Relationship-Learning for Speech Emotion Recognition via Transformers. [PDF]
Sensors (Basel)Li H, Li J, Liu H, Liu T, Chen Q, You X.
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Prediction of Arteriovenous Access Dysfunction by Mel Spectrogram-based Deep Learning Model. [PDF]
Int J Med SciChung TL +8 more
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Intelligent Localization of Cross-Sectional Structural Damage in Molten Salt Receiver Tubes Using Mel Spectrograms and TSA-Optimized 2D-CNN. [PDF]
Sensors (Basel)Leng P +5 more
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A lightweight CNN-transformer hybrid architecture with channel attention for real-time hazardous acoustic event detection. [PDF]
Front Artif IntellAltayeva A, Omarov N.
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Prediction of cognitive impairment through speech data analysis: A comparative evaluation of deep learning models. [PDF]
PLoS OneKim M +8 more
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