MFCC feature extraction with librosa Multiple model architectures (CNN, LSTM, CNN-LSTM hybrid) Support for datasets: RAVDESS, TESS, EMO-DB Real-time emotion prediction ...

In a dual-center cross-sectional study (N = 202), Center 1 (Capital Center for Children’s Health, Capital Medical University, n = 161) served as the development cohort and Center 2 (College of ...

Mental disorders have a significant impact on many areas of people’s life, particularly on affective regulation; thus, there is a growing need to find disease-specific biomarkers to improve early ...

feature_extraction_functions.py: a set of feature extraction functions from RDShi-SpeakerCount. MFCC: Mel-frequency cepstral coefficients calculation. MFCC.py ...

Abstract: Aiming at the shortcomings of traditional single feature extraction methods in representing speech features, this paper proposes a speaker recognition method that combines Mel frequency ...

Abstract: The Mel-Frequency Cepstral Coefficients (MFCC) feature extraction method is a leading approach for speech feature extraction and current research aims to identify performance enhancements.