Fixed frequency range empirical wavelet transform based acoustic and entropy features for speech emotion recognition
Authors:
- Siba Prasad MishraSMSiba Prasad Mishra
- Pankaj WarulePWPankaj Warule
- Suman DebSDSuman Deb
- 14 November 2024
- journal article
- research article
- Published by Elsevier in Speech Communication
- Vol. 166
Abstract
No abstract availableKeywords
This publication has 55 references indexed in Scilit:
- Speech emotion classification using feature-level and classifier-level fusionEvolving Systems, 2023
- Speech emotion recognition using MFCC-based entropy featureSignal, Image and Video Processing, 2023
- A statistical feature extraction for deep speech emotion recognition in a bilingual scenarioMultimedia Tools and Applications, 2022
- Analysis of complexity in the EEG activity of Parkinson’s disease patients by means of approximate entropyGeroScience, 2022
- Emotion classification from speech signal based on empirical mode decomposition and non-linear featuresComplex & Intelligent Systems, 2021
- Pitch-synchronous single frequency filtering spectrogram for speech emotion recognitionMultimedia Tools and Applications, 2020
- A novel feature selection method for speech emotion recognitionApplied Acoustics, 2019
- Detection of Shockable Ventricular Arrhythmia using Variational Mode DecompositionJournal of Medical Systems, 2016
- Acoustic Emotion Recognition for Affective Computer Gaming2008
- Specific respiratory patterns distinguish among human basic emotionsInternational Journal of Psychophysiology, 1991