Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Emotional Expression01:26

Emotional Expression

Emotional expression encompasses how individuals convey their emotions through verbal communication and non-verbal cues. These non-verbal actions include facial expressions, body language, and physical gestures, such as frowning or smiling. Among these, facial expressions play a crucial role in emotional expression and are understood universally, indicating a biological basis for how humans communicate emotions.
Universal Facial Expressions
Psychologist Paul Ekman identified seven basic...
Facial Feedback Hypothesis01:24

Facial Feedback Hypothesis

Charles Darwin proposed that facial expressions are an evolutionary adaptation for communication. He argued that these expressions are not influenced by culture but are universal across species. For example, a snarling expression with exposed teeth signals a threat in many animals, including humans. Darwin also suggested that displaying an emotion can intensify the feeling. Smiling, for example, could enhance one's sense of happiness. This idea laid the foundation for understanding the role of...
Muscles for Facial Expressions01:14

Muscles for Facial Expressions

The craniofacial muscles are a collection of approximately 20 thin skeletal muscles situated beneath the skin of the face and scalp. These muscles, primarily responsible for the vast array of human facial expressions, originate from the bones or fibrous structures of the skull and extend outwards to connect with the skin. While most skeletal muscles in the body are enveloped in thick fascia, facial muscles generally have a more delicate fascial covering, with the buccinator muscle being a...
Labeling Emotion01:20

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 Emotion01:20

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...
Motional Emf01:22

Motional Emf

Magnetic flux depends on three factors: the strength of the magnetic field, the area through which the field lines pass, and the field's orientation with respect to the surface area. If any of these quantities vary, a corresponding variation in magnetic flux occurs. If the area through which the magnetic field lines are passing changes, then the magnetic flux also changes. This change in the area can be of two types: the flux through the rectangular loop increases as it moves into the magnetic...

You might also read

Related Articles

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

Sort by
Same author

Exemestane chronic exposure induces cardiotoxicity via disrupting calcium homeostasis and endothelin pathway: Evidence from biochemical, radiological and histopathological analyses.

The Journal of steroid biochemistry and molecular biology·2026
Same author

SuperiorGAT: graph attention networks for sparse LiDAR point cloud reconstruction in autonomous systems.

Scientific reports·2026
Same author

Correction: Rao et al. Ensemble Deep-Learning-Based Prognostic and Prediction for Recurrence of Sporadic Odontogenic Keratocysts on Hematoxylin and Eosin Stained Pathological Images of Incisional Biopsies. <i>J. Pers. Med.</i> 2022, <i>12</i>, 1220.

Journal of personalized medicine·2026
Same author

Multi-Species Probiotics Improve Health Performance and Alleviate Stress Responses of Rohu (Labeo rohita) in Inland Brackish Water Ponds.

Probiotics and antimicrobial proteins·2026
Same author

Structure-based computational screening and molecular dynamics reveal potential inhibitors of Norovirus VP1 and RdRp Proteins: an in-silico study.

Scientific reports·2026
Same author

Exosomes in Cancer Biology: Emerging Biomarkers and Therapeutic Targets.

Journal of Cancer·2026

Related Experiment Video

Updated: Jul 2, 2026

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

Emotionally expressive facial animation driven by EmotionBERT embeddings.

Tahani Jaser Alahmadi1, Galiya Ybytayeva2,3, Harbi AlMahafzah4

  • 1Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

Scientific Reports
|July 1, 2026
PubMed
Summary

Speech2Face synthesizes realistic facial animations from speech, enhancing emotional accuracy by 80.8%. This novel framework improves engagement in virtual reality and digital human applications.

Keywords:
Emotion embeddingsEmotion-aware animationLarge language modelsMultimodal synthesisSpeech-driven facial animation

More Related Videos

Exploring the Use of Isolated Expressions and Film Clips to Evaluate Emotion Recognition by People with Traumatic Brain Injury
05:51

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: Jul 2, 2026

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

Exploring the Use of Isolated Expressions and Film Clips to Evaluate Emotion Recognition by People with Traumatic Brain Injury
05:51

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 Vision
  • Natural Language Processing
  • Affective Computing

Background:

  • Facial animation driven by speech is crucial for virtual reality (VR), human-computer interaction (HCI), and entertainment.
  • Existing methods often fail to capture the full emotional and semantic nuances of speech, leading to less immersive experiences.

Purpose of the Study:

  • To introduce Speech2Face, a framework for synthesizing high-fidelity facial movements directly from expressive speech.
  • To improve the emotional accuracy, naturalness, and synchronization of speech-driven facial animation.

Main Methods:

  • Utilized EmotionBERT for extracting semantic and emotional embeddings from speech transcripts.
  • Developed a framework for generating temporally coherent and contextually appropriate facial expressions conditioned on speech inputs.
  • Evaluated performance on VOCASET, IEMOCAP, MEAD, and BIWI datasets.

Main Results:

  • Achieved significant improvements in emotional accuracy, with gains up to 80.8% compared to existing models.
  • Demonstrated enhanced naturalness and synchronization between synthesized facial movements and speech.
  • Validated the framework's effectiveness across multiple benchmark datasets.

Conclusions:

  • Speech2Face offers an effective solution for multi-modal emotion-aware synthesis.
  • The framework advances the creation of engaging and realistic digital humans by better capturing vocal expressivity.