Scientific Research Publishing

Cybersecurity and Forensic Audio Analysis: Deepfake Detection Based on Mfcc, Audio-Text Disconsistency, and Prosodic Features ()

1 Department of Computer and Instructional Technologies Education, Gazi Faculty of Education, Gazi University, Ankara, Türkiye. 2 Department of Forensic Informatics, Institute of Informatics, Gazi ...
GitHub

Ranjeet7680/-Speech-Emotion-Recognition

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

Mobile Application for Stress Detection via MFCC Speech-Features

Abstract: Everyone goes through periods of mental stress in their daily lives. While small amounts of stress can enhance focus, alertness, and performance, excessive stress negatively affects ...
GitHub

Speech Feature Extraction

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

A novel approach for MFCC feature extraction

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.