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

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

Temporal patterns in articulation underlying repetitions, prolongations and blocks.

Journal of fluency disorders·2026
Same author

Endoscopic Ultrasound fine-needle aspiration and cystic fluid analysis in patients with pancreatic cystic lesions.

Best practice & research. Clinical gastroenterology·2026
Same author

Depression, speech intelligibility, and articulatory coordination.

The Journal of the Acoustical Society of America·2026
Same author

Perceptual Ratings Predict Speech Inversion Articulatory Kinematics in Childhood Speech Sound Disorders.

Journal of speech, language, and hearing research : JSLHR·2026
Same author

Correction: Slower respiration rate is associated with higher self-reported well-being after wellness training.

Scientific reports·2026
Same author

Endoscopic management for gastrointestinal leaks, perforations, and fistulae: Technical tips and outcomes.

World journal of gastrointestinal endoscopy·2026
Same journal

High-resolution depth estimation for multiple wideband sources in deep sea via sparse Bayesian learninga).

The Journal of the Acoustical Society of America·2026
Same journal

Depression markers in speech: An approach based on tract variables dynamics.

The Journal of the Acoustical Society of America·2026
Same journal

The oyster toadfish (Opsanus tau) alters active and diurnal calling amid vessel noise in New York City.

The Journal of the Acoustical Society of America·2026
Same journal

Experimental noise characterisation of phase-locked tandem-rotor in edgewise flight.

The Journal of the Acoustical Society of America·2026
Same journal

The tune-text-temporal synergy: Prosodic effects of final segmental weakening in Neapolitan.

The Journal of the Acoustical Society of America·2026
Same journal

Monitoring vessel movement above critical offshore infrastructure using distributed acoustic sensing.

The Journal of the Acoustical Society of America·2026
See all related articles

Related Experiment Video

Updated: May 24, 2026

Examining Gesture Production in the Presence of Communication Challenges
07:18

Examining Gesture Production in the Presence of Communication Challenges

Published on: January 26, 2024

Recognizing articulatory gestures from speech for robust speech recognition.

Vikramjit Mitra1, Hosung Nam, Carol Espy-Wilson

  • 1Speech Technology and Research Laboratory, SRI International, Menlo Park, California 94025, USA.

The Journal of the Acoustical Society of America
|March 20, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a novel neural network for recognizing articulatory gestures from speech. Incorporating these recognized gestures significantly enhances automatic speech recognition performance, especially in noisy conditions.

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: May 24, 2026

Examining Gesture Production in the Presence of Communication Challenges
07:18

Examining Gesture Production in the Presence of Communication Challenges

Published on: January 26, 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:

  • Speech Processing
  • Machine Learning
  • Bioacoustics

Background:

  • Automatic speech recognition (ASR) systems benefit from articulatory information, which is not directly observable.
  • Estimating articulatory gestures from speech signals is crucial for improving ASR accuracy.

Purpose of the Study:

  • To develop a neural network system for recognizing articulatory gestures from speech.
  • To integrate recognized articulatory gestures into a speech recognition system for enhanced performance.

Main Methods:

  • A novel neural network architecture was proposed for articulatory gesture recognition.
  • The system was evaluated in three stages: synthetic data, natural speech waveforms, and a Dynamic Bayesian Network.

Main Results:

  • Estimated tract-variable-time-functions improved gesture recognition on synthetic data.
  • Recognized gestures enhanced the noise-robustness of word recognition systems.
  • Gesture-based systems outperformed acoustic-only systems in word recognition tasks.

Conclusions:

  • The proposed system effectively recognizes articulatory gestures from speech.
  • Integrating recognized gestures into ASR systems improves performance and noise robustness.