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

Depressive Disorders: MDD and Dysthymia01:27

Depressive Disorders: MDD and Dysthymia

1.1K
Depressive disorders are a group of mental health conditions characterized by pervasive feelings of sadness, diminished pleasure in life, and a significant impact on daily functioning. These conditions are most prevalent in individuals during their 30s and affect women at twice the rate of men. Contrary to popular belief, younger individuals are generally more susceptible to these disorders than older adults. Two key types of depressive disorders include Major Depressive Disorder (MDD) and...
1.1K
Depressive Disorders: Etiology01:27

Depressive Disorders: Etiology

842
Depressive disorders result from a complex interplay of biological, psychological, and sociocultural factors, each contributing uniquely to the development and persistence of the condition. Understanding these factors provides critical insight into the multifaceted nature of depression.
Biological Factors in Depression
Biological predispositions significantly influence the risk of developing depressive disorders. Genetic studies highlight the role of variations in the serotonin transporter...
842
Long-term Depression01:03

Long-term Depression

3.5K
Long-term depression, or LTD, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTD is the process of synaptic weakening that occurs over time between pre and postsynaptic neuronal connections. The synaptic weakening of LTD works in opposition to synaptic strengthening by long-term potentiation (LTP) and together are the main mechanisms that underlie learning and memory.
Calcium Ion Concentration Mechanism
If over...
3.5K
Long-term Depression01:05

Long-term Depression

33.7K
Long-term depression, or LTD, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTD is the process of synaptic weakening that occurs over time between pre and postsynaptic neuronal connections. The synaptic weakening of LTD works in opposition to synaptic strengthening by long-term potentiation (LTP) and together are the main mechanisms that underlie learning and memory.
33.7K
Depression: Overview01:18

Depression: Overview

1.2K
Depression is a prevalent mental illness marked by persistent sadness and lack of interest in previously enjoyable activities. It can take several forms, including major depression, persistent depressive disorder, and bipolar I and II disorders. Symptoms range from emotional changes like chronic worry to physical changes like sleep disturbances and suicidal thoughts. From a neurobiological perspective, depression is believed to be triggered by abnormalities in the brain's prefrontal cortex,...
1.2K
Non-Verbal Cues01:29

Non-Verbal Cues

433
Non-verbal communication extends beyond gestures and facial expressions to include vocal elements known as paralanguage. Paralanguage consists of non-verbal vocal cues such as pitch, loudness, speech rate, pauses, and non-verbal vocalizations like laughter, sighs, and moans. These elements not only accompany speech but also provide critical emotional and contextual information.The Role of Paralanguage in CommunicationParalanguage adds depth to spoken language by conveying emotions and...
433

You might also read

Related Articles

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

Sort by
Same author

Representation Learning for Interpersonal and Multimodal Behavior Dynamics: A Multiview Extension of Latent Change Score Models.

Proceedings of the ... ACM International Conference on Multimodal Interaction. ICMI (Conference)·2025
Same author

Beyond Additive Fusion: Learning Non-Additive Multimodal Interactions.

Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing·2025
Same author

Computational Analysis of Expressive Behavior in Clinical Assessment.

Annual review of clinical psychology·2025
Same author

Dynamic and dyadic relationships between facial behavior, working alliance, and treatment outcomes during depression therapy.

Journal of consulting and clinical psychology·2025
Same author

Advances in Behavioral Science Using Automated Facial Image Analysis and Synthesis.

IEEE signal processing magazine·2025
Same author

How Still? Parent-Infant Interaction During the Still-Face and Later Infant Attachment.

Infant and child development·2025
Same journal

Describe Where You Are: Improving Noise-Robustness for Speech Emotion Recognition with Text Description of the Environment.

IEEE transactions on affective computing·2026
Same journal

Rethinking Emotion Annotations in the Era of Large Language Models.

IEEE transactions on affective computing·2026
Same journal

Datasets of Smartphone Modalities for Depression Assessment: A Scoping Review.

IEEE transactions on affective computing·2025
Same journal

Wearable Sensor-based Multimodal Physiological Responses of Socially Anxious Individuals in Social Contexts on Zoom.

IEEE transactions on affective computing·2025
Same journal

Mechanoreceptive Aβ primary afferents discriminate naturalistic social touch inputs at a functionally relevant time scale.

IEEE transactions on affective computing·2025
Same journal

Emotion Recognition in the Real-World: Passively Collecting and Estimating Emotions from Natural Speech Data of Individuals with Bipolar Disorder.

IEEE transactions on affective computing·2025
See all related articles

Related Experiment Video

Updated: Mar 24, 2026

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

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

Published on: August 9, 2024

2.1K

Detecting Depression Severity from Vocal Prosody.

Ying Yang1, Catherine Fairbairn2, Jeffrey F Cohn3

  • 1Rehabilitation and Neural Engineering Laboratory, University of Pittsburgh. yiy17@pitt.edu.

IEEE Transactions on Affective Computing
|March 18, 2016
PubMed
Summary
This summary is machine-generated.

Vocal prosody analysis accurately reflects depression severity changes over time. This method shows potential for aiding in depression screening and monitoring during treatment and recovery.

Keywords:
Hierarchical Linear Modeling (HLM)Prosodydepressioninterpersonal influenceswitching pausevocal fundamental frequency

More Related Videos

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment
05:19

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment

Published on: July 7, 2023

3.7K
Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

1.2K

Related Experiment Videos

Last Updated: Mar 24, 2026

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

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

Published on: August 9, 2024

2.1K
Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment
05:19

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment

Published on: July 7, 2023

3.7K
Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

1.2K

Area of Science:

  • Psychiatry
  • Clinical Psychology
  • Speech Science

Background:

  • Depression severity fluctuates over time and impacts communication.
  • Vocal prosody, encompassing tone and rhythm, may reflect emotional states.
  • Objective measures are needed to track depression symptom changes.

Purpose of the Study:

  • To examine the relationship between vocal prosody and depression severity.
  • To determine if vocal characteristics can predict changes in depression.
  • To investigate interpersonal vocal effects in the context of depression.

Main Methods:

  • Analysis of vocal prosody (timing, fundamental frequency) in 57 Major Depressive Disorder patients.
  • Perceptual judgments by naive listeners on vocal recordings.
  • Quantitative analysis of speech patterns during clinical interviews over time.

Main Results:

  • Naive listeners could perceive depression severity from vocal cues.
  • Quantitative vocal prosody features correlated with depression severity changes.
  • Interviewer vocal prosody also showed corresponding effects.
  • Vocal prosody explained 60% of the variation in depression scores.
  • Accurate detection of depression severity ranges (low, mild, moderate-to-severe) in 69% of cases.

Conclusions:

  • Vocal prosody analysis is a promising tool for depression screening.
  • Monitoring vocal changes can assist in tracking depression over time.
  • This non-invasive method may support clinical assessment and treatment monitoring.