Jove
Visualize
Contact Us

Related Concept Videos

Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

777
The human brain perceives pitch through two primary mechanisms reflected in place theory and frequency theory. Each mechanism describes how sound waves are interpreted as specific pitches by the brain, offering insights into the intricate processes of auditory perception.
Place theory, or place coding, suggests that different pitches are heard because various sound waves activate specific locations along the cochlea's basilar membrane. The brain determines the pitch of a sound by...
777
Labeling Emotion01:20

Labeling Emotion

508
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...
508

You might also read

Related Articles

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

Sort by
Same author

Editorial: Ethical design of artificial intelligence-based systems for decision making.

Frontiers in artificial intelligence·2023
Same author

Lie to Me: Shield Your Emotions from Prying Software.

Sensors (Basel, Switzerland)·2022
Same author

Can we predict continued pessary use as primary treatment in women with symptomatic pelvic organ prolapse (POP)? A prospective cohort study.

International urogynecology journal·2021
Same author

Enhancing Mouth-Based Emotion Recognition Using Transfer Learning.

Sensors (Basel, Switzerland)·2020
Same author

Surgery for cystocele I--questions.

International urogynecology journal·2012
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 Experiment Video

Updated: Dec 11, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

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

Published on: December 15, 2023

5.0K

Emotional sounds of crowds: spectrogram-based analysis using deep learning.

Valentina Franzoni1, Giulio Biondi2, Alfredo Milani1

  • 1Department of Mathematics and Computer Science, University of Perugia, Perugia, Italy.

Multimedia Tools and Applications
|August 25, 2020
PubMed
Summary
This summary is machine-generated.

This study explores classifying crowd emotions from audio using deep learning. The developed technique shows promising results in identifying collective emotional states from crowd sounds.

Keywords:
CNNCrowd computingCrowd emotionsEmotion recognitionImage recognitionTransfer learning

More Related Videos

Semi-Automated Analysis of Peak Amplitude and Latency for Auditory Brainstem Response Waveforms Using R
06:01

Semi-Automated Analysis of Peak Amplitude and Latency for Auditory Brainstem Response Waveforms Using R

Published on: December 9, 2022

2.8K
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

1.9K

Related Experiment Videos

Last Updated: Dec 11, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

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

Published on: December 15, 2023

5.0K
Semi-Automated Analysis of Peak Amplitude and Latency for Auditory Brainstem Response Waveforms Using R
06:01

Semi-Automated Analysis of Peak Amplitude and Latency for Auditory Brainstem Response Waveforms Using R

Published on: December 9, 2022

2.8K
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

1.9K

Area of Science:

  • Computational Social Science
  • Affective Computing
  • Machine Learning

Background:

  • Crowds exhibit collective emotions, observable through vocalizations like cheering or booing.
  • Analyzing crowd emotions presents a unique challenge compared to individual emotion recognition.

Purpose of the Study:

  • To investigate if crowd sound's emotional content can be characterized by frequency-amplitude features.
  • To develop and evaluate a deep learning model for classifying crowd emotions from audio data.

Main Methods:

  • Generated sound spectrograms from fixed-length audio fragments of crowd sounds.
  • Applied transfer learning using a convolutional neural network (CNN) pre-trained on the ImageNet dataset.
  • Filtered and normalized audio clips before spectrogram generation and fine-tuned the CNN model.

Main Results:

  • The proposed technique successfully generated spectrograms from crowd sound fragments.
  • The fine-tuned CNN model demonstrated promising performance in classifying crowd emotions.
  • Frequency-amplitude features were found to be relevant for characterizing crowd emotions.

Conclusions:

  • The study validates the potential of using audio analysis and deep learning for crowd emotion recognition.
  • The developed method offers a novel approach to understanding collective emotional dynamics in public gatherings.
  • Further research can refine the model for broader applications in social event analysis.