Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Labeling Emotion

Labeling Emotion

Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...

Physiology of Emotion

Physiology of Emotion

The physiology of emotions is a multifaceted process involving the autonomic nervous system, brain structures, hormones, and neurotransmitters. This intricate interplay dictates how emotions manifest in the body and influence behavior.
Autonomic Nervous System
The autonomic nervous system (ANS) plays a critical role in emotional responses by regulating involuntary physiological functions. It consists of two main components: the sympathetic and parasympathetic systems. The sympathetic system...

Empathy

Empathy

Some researchers suggest that altruism operates on empathy. Empathy is the capacity to understand another person’s perspective, to feel what he or she feels. An empathetic person makes an emotional connection with others and feels compelled to help (Batson, 1991). Empathy can be expressed in several ways, including cognitive, affective, and motor.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Building a Gender-Bias-Resistant Super Corpus as a Deep Learning Baseline for Speech Emotion Recognition.

Sensors (Basel, Switzerland)·2025

Same author

Automatic Quantification of Atmospheric Turbulence Intensity in Space-Time Domain.

Sensors (Basel, Switzerland)·2025

Same author

Transfer Learning Video Classification of Preserved, Mid-Range, and Reduced Left Ventricular Ejection Fraction in Echocardiography.

Diagnostics (Basel, Switzerland)·2024

Same author

Hybrid Classical-Quantum Transfer Learning for Cardiomegaly Detection in Chest X-rays.

Journal of imaging·2023

Same author

Classifying Comments on Social Media Related to Living Kidney Donation: Machine Learning Training and Validation Study.

JMIR medical informatics·2022

Same author

Making Cities Smarter-Optimization Problems for the IoT Enabled Smart City Development: A Mapping of Applications, Objectives, Constraints.

Sensors (Basel, Switzerland)·2022

Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026

Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026

Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026

Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026

Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026

Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Nov 17, 2025

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

Deep Learning Techniques for Speech Emotion Recognition, from Databases to Models.

Babak Joze Abbaschian¹, Daniel Sierra-Sosa¹, Adel Elmaghraby¹

¹Computer Science and Engineering Department, University of Louisville Louisville, KY 40292, USA.

Sensors (Basel, Switzerland)

|February 13, 2021

Summary

This summary is machine-generated.

This study surveys deep learning and conventional methods for Speech Emotion Recognition (SER). It compares neural network approaches to advance human-computer interaction through accurate, real-time emotion detection.

Keywords:

CNN GAN LSTM attention mechanism autoencoders deep learning emotional speech database machine learning speech emotion recognition

More Related Videos

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Exploring the Use of Isolated Expressions and Film Clips to Evaluate Emotion Recognition by People with Traumatic Brain Injury

Exploring the Use of Isolated Expressions and Film Clips to Evaluate Emotion Recognition by People with Traumatic Brain Injury

Published on: May 15, 2016

Related Experiment Videos

Last Updated: Nov 17, 2025

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Exploring the Use of Isolated Expressions and Film Clips to Evaluate Emotion Recognition by People with Traumatic Brain Injury

Exploring the Use of Isolated Expressions and Film Clips to Evaluate Emotion Recognition by People with Traumatic Brain Injury

Published on: May 15, 2016

Area of Science:

Computer Science, Artificial Intelligence, Machine Learning

Background:

Growing need for accurate, real-time Speech Emotion Recognition (SER) in human-computer interaction.
Advancements in neural networks necessitate a review of current SER methodologies.

Purpose of the Study:

To provide a comprehensive survey of discrete Speech Emotion Recognition (SER).
To compare deep learning and conventional machine learning techniques for SER.
To analyze available datasets and practical neural network approaches in SER.

Main Methods:

Review of deep learning approaches for SER.
Review of conventional machine learning techniques for speech emotion recognition.
Multi-aspect comparison of neural network approaches in SER.

Main Results:

Identification of key deep learning and conventional methods in SER.
Comparative analysis of different SER approaches and datasets.
Highlighting practical neural network applications in emotion recognition from speech.

Conclusions:

A clearer understanding of the current state of discrete SER.
Guidance on selecting feasible methods for accurate, real-time SER.
Foundation for future research in speech emotion recognition for enhanced human-computer interaction.