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...
Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

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 identifying...

You might also read

Related Articles

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

Sort by
Same author

An Expectation Maximization approach to Joint Modeling of Multidimensional Ratings derived from Multiple Annotators.

Interspeech·2026
Same author

Developing personalized algorithms for sensing mental health symptoms in daily life.

Npj mental health research·2025
Same author

Association of machine-learning-rated supportive counseling skills with psychotherapy outcome.

Journal of consulting and clinical psychology·2025
Same author

Vertical larynx actions and intergestural timing stability in Hausa ejectives and implosives.

Phonetica·2024
Same author

People make mistakes: Obtaining accurate ground truth from continuous annotations of subjective constructs.

Behavior research methods·2024
Same author

Multimodal analysis of temporal affective variability within treatment for depression.

Journal of consulting and clinical psychology·2024

Related Experiment Video

Updated: Jun 21, 2026

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
09:09

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

Exploiting Acoustic and Syntactic Features for Automatic Prosody Labeling in a Maximum Entropy Framework.

Vivek Kumar Rangarajan Sridhar1, Srinivas Bangalore, Shrikanth S Narayanan

  • 1The Viterbi School of Engineering, Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089-2564 USA (e-mail: vrangara@usc.edu ; shri@sipi.usc.edu ).

IEEE Transactions on Audio, Speech, and Language Processing
|July 16, 2009
PubMed
Summary

This study introduces a new automatic prosody labeling framework using maximum entropy modeling. It accurately detects pitch accents and phrase structures, improving upon previous methods for speech analysis.

More Related Videos

Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis
05:48

Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis

Published on: August 9, 2024

Related Experiment Videos

Last Updated: Jun 21, 2026

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
09:09

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis
05:48

Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis

Published on: August 9, 2024

Area of Science:

  • Computational Linguistics
  • Speech Processing
  • Natural Language Processing

Background:

  • Automatic prosody labeling is crucial for understanding speech.
  • Existing methods often struggle to integrate diverse linguistic and acoustic information effectively.

Purpose of the Study:

  • To develop a maximum entropy-based framework for automatic prosody labeling.
  • To enhance the detection of prominence and phrase structures using the Tones and Break Indices (ToBI) scheme.

Main Methods:

  • Utilized a maximum entropy model integrating language and speech data.
  • Incorporated novel syntactic features (supertags) and quantized acoustic-prosodic features.
  • Employed discriminative training for robust feature selection.

Main Results:

  • Achieved high accuracies for pitch accent (86.0%-93.1%) and boundary tone detection (79.8%-90.3%) across two corpora.
  • Demonstrated strong performance in phrase structure detection via prosodic break index labeling (84%-87%).
  • Results significantly outperformed previous benchmarks.

Conclusions:

  • The maximum entropy acoustic-syntactic model effectively integrates lexical, syntactic, and acoustic features for prosody detection.
  • The proposed framework offers a robust and accurate solution for automatic prosody labeling.