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

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...
Non-Verbal Cues01:29

Non-Verbal Cues

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...

You might also read

Related Articles

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

Sort by
Same author

Effect of body mass index and age on the prognosis of non-metastatic nasopharyngeal carcinoma.

BMC cancer·2026
Same author

Predicting response to neoadjuvant therapy in breast cancer using longitudinal DCE-MRI deep learning integrated with tumor microenvironment data.

Frontiers in immunology·2026
Same author

Stratified prediction of HER2 status in breast cancer by integrating intratumoral and peritumoral radiomics from DCE-MRI.

BMC cancer·2026
Same author

Navigating Structural Tensions: Australian Surrogacy Facilitators' Understanding on Children's Rights in Cross-Border Surrogacy.

Asian bioethics review·2026
Same author

Systematic Review and Meta-Analysis on Heavy Metals and Trace Elements in Mild Cognitive Impairment.

Biological trace element research·2025
Same author

Real-time Instantaneous Phase Estimation Using a Deep Dual-Branch Complex Neural Network.

IEEE transactions on bio-medical engineering·2025

Related Experiment Video

Updated: May 22, 2026

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology
05:38

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology

Published on: June 29, 2021

2.8K

CIRE: A Chinese EEG Dataset for decoding speech intention modulated by prosodic emotion.

Shengrui He1, Zhongjie Li2, Jianwu Dang1,3

  • 1Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, 300350, Tianjin, China.

Scientific Data
|October 21, 2025
PubMed
Summary

This study introduces the CIRE dataset for decoding speech intention using electroencephalography (EEG). It enables research into diverse intentions behind identical text, advancing brain-computer interface (BCI) technology.

More Related Videos

Author Spotlight: Investigating Vocal Information Representation in Small Primates and Its Alteration by Psychiatric Disorders Using Noninvasive EEG
07:52

Author Spotlight: Investigating Vocal Information Representation in Small Primates and Its Alteration by Psychiatric Disorders Using Noninvasive EEG

Published on: July 26, 2024

1.3K
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

2.0K

Related Experiment Videos

Last Updated: May 22, 2026

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology
05:38

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology

Published on: June 29, 2021

2.8K
Author Spotlight: Investigating Vocal Information Representation in Small Primates and Its Alteration by Psychiatric Disorders Using Noninvasive EEG
07:52

Author Spotlight: Investigating Vocal Information Representation in Small Primates and Its Alteration by Psychiatric Disorders Using Noninvasive EEG

Published on: July 26, 2024

1.3K
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

2.0K

Area of Science:

  • Cognitive Neuroscience
  • Neurotechnology
  • Speech Processing

Background:

  • Decoding speech intention is crucial for brain-computer interface (BCI) advancement.
  • Existing datasets lack diversity in decoding speech intentions from identical text.
  • Prosodic emotion significantly influences the interpretation of spoken language.

Purpose of the Study:

  • To introduce the CIRE dataset for spoken language interaction intention.
  • To facilitate research on decoding nuanced speech intentions.
  • To support advancements in BCI and cognitive neuroscience.

Main Methods:

  • Collected high-density (128-channel) EEG data from 38 participants.
  • Utilized Wav2vec2-derived acoustic embeddings for speech stimuli.
  • Applied signal processing, cognitive analysis, and machine learning for validation.

Main Results:

  • Achieved a 68.2% cross-subject classification accuracy with a baseline model.
  • Identified interpretable neurophysiological correlates for intention differences.
  • Demonstrated the dataset's utility in cognitive neuroscience and BCI.

Conclusions:

  • The CIRE dataset addresses the need for diverse speech intention data.
  • High-density EEG data supports cognitive neuroscience and speech BCI applications.
  • Findings contribute to brain-inspired algorithms and BCI development.