A new study developed a snore-source classification model that uses STFT spectrograms, pretrained CNN features, and an L2-regularized SVM to identify where snoring originates in the upper airway.

cisc-867 deep learning course project. speech emotion recognition (ser) on ravdess using a lightweight 1d cnn on log-mel-spectrograms, compared against a classical mfcc + svm baseline. optimized for ...

Voice audio was processed into Log-Mel spectrograms. Pre-trained convolutional neural networks (CNNs), including VGG16, ResNet50, and DenseNet161, were employed for transfer learning to perform both ...