Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Detection of Gross Error: The Q Test

Detection of Gross Error: The Q Test

When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...

Difference from Background: Limit of Detection

Difference from Background: Limit of Detection

The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...

Perceiving Loudness, Pitch, and Location

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...

Force Classification

Force Classification

Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...

Air-entraining Agents

Air-entraining Agents

Air-entraining agents improve the durability and workability of concrete in climates with frequent freezing and thawing. These agents prevent cracks by introducing small air bubbles into the mix, creating spaces accommodating water expansion when temperatures drop. The air-entraining agents lower the surface tension of water, forming stable, small air bubbles. This method is more effective than having accidental large voids, as the intentional, smaller, and evenly distributed air voids improve...

You might also read

Related Articles

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

Sort by

Same author

Exploring spillover effects following surgical de-implementation: an observational evaluation of primary care, referrals, and time to surgical intervention following reductions in the use of tonsillectomy and Dupuytren's contracture.

Implementation science communications·2026

Same author

Change in the prevalence of creaky voice over time in Australian English.

JASA express letters·2025

Same author

Perceptual Style-Shifting Across Singing and Speech: Music Activates Pop Song English for NZ Listeners.

Language and speech·2025

Same author

Electroglottographic analysis of coda voicelessness in Australian English.

The Journal of the Acoustical Society of America·2025

Same author

Delivering a national de-adoption programme: a documentary analysis of local commissioning policy compliance with England's Evidence-based Interventions programme (EBI).

BMC health services research·2025

Same author

Relevance and flexibility are key: exploring healthcare managers' views and experiences of a de-adoption programme in the English National Health Service.

BMC health services research·2025

Search research articles

Related Experiment Video

Updated: Aug 27, 2025

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

Evaluating automatic creaky voice detection methods.

Hannah White¹, Joshua Penney¹, Andy Gibson¹

¹Centre for Language Sciences, Department of Linguistics, Macquarie University, Sydney, New South Wales, Australia.

The Journal of the Acoustical Society of America

|October 1, 2022

Summary

This summary is machine-generated.

This study compares automatic creaky voice detection tools, finding that combining methods and analyzing sonorants improves accuracy. Results offer efficient solutions for large-scale creaky voice research.

More Related Videos

Targeted Training of Ultrasonic Vocalizations in Aged and Parkinsonian Rats

Targeted Training of Ultrasonic Vocalizations in Aged and Parkinsonian Rats

Published on: August 8, 2011

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

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

Published on: August 9, 2024

Related Experiment Videos

Last Updated: Aug 27, 2025

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

Targeted Training of Ultrasonic Vocalizations in Aged and Parkinsonian Rats

Targeted Training of Ultrasonic Vocalizations in Aged and Parkinsonian Rats

Published on: August 8, 2011

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

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

Published on: August 9, 2024

Area of Science:

Phonetics and Speech Science
Acoustic Phonetics
Computational Linguistics

Background:

Growing research interest in non-modal voice quality, specifically creaky voice.
Manual annotation of creaky voice is time-consuming, necessitating automatic detection methods.
Existing automatic methods utilize diverse acoustic cues for creak detection.

Purpose of the Study:

To compare the performance of three automatic creaky voice detection tools: AntiMode, Creak Detector, and Roughness.
To investigate the efficacy of combining these tools for enhanced creak detection accuracy.
To identify strategies for improving automatic creak detection, particularly for large-scale studies.

Main Methods:

Comparison of AntiMode, Creak Detector, and Roughness algorithms against manual annotation.
Utilized speech data from 80 Australian English speakers.
Explored the impact of combining tools and restricting analysis to sonorant segments.

Main Results:

Combining automatic tools can yield more accurate creak detection than individual tools.
Restricting analysis to sonorant segments significantly improves automatic creak detection performance.
Tools performed more consistently on female speech compared to male speech.

Conclusions:

The study provides practical options for researchers, including combining automatic tools for improved creak detection.
Optimizing detection via a creak probability threshold sweep is recommended before applying the Creak Detector algorithm.
Findings support efficient, large-scale research on creaky voice by offering promising automated solutions.