Related Experiment Video
Updated: Oct 1, 2025
A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions
Published on: July 16, 2015
A context-based approach to predict speech intelligibility in interrupted noise: Model design.
Jelmer van Schoonhoven1, Koenraad S Rhebergen2, Wouter A Dreschler1
1Department of Clinical and Experimental Audiology, Amsterdam University Medical Center, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands.
Improving speech intelligibility predictions, this study enhanced the Extended Speech Transmission Index (ESTI) by calculating it per phoneme and integrating context models. This new method boosts accuracy, particularly in low-frequency noise conditions.
Area of Science:
- Acoustics
- Speech Perception
- Signal Processing
Background:
- The Extended Speech Transmission Index (ESTI) effectively predicts speech intelligibility in fluctuating noise.
- However, ESTI accuracy decreases with low masker modulation frequencies (<8 Hz).
Purpose of the Study:
- To enhance speech intelligibility prediction models.
- To improve accuracy for maskers with low modulation frequencies.
Main Methods:
- Calculated ESTI per phoneme to estimate phoneme intelligibility.
- Integrated the ESTI model with context models (Boothroyd and Nittrouer, Bronkhorst et al.).
- Validated the approach using interrupted speech data.
Main Results:
- The combined ESTI and context model approach improved prediction accuracy.
- Significant improvements were observed for maskers with interruption rates below 5 Hz.
Conclusions:
- Calculating ESTI at the phoneme level combined with a context model is a viable strategy.
- This method enhances the prediction of speech intelligibility, especially in challenging noise conditions.
More Related Videos
08:32Examining Online Syntactic Processing of Spoken Complex Sentences in Chinese Using Dual-Modal Interference Tasks
Published on: September 5, 2019
14:05Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses
Published on: January 23, 2017
Related Concept Videos
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
00:53Sound Waves: Interference
01:06Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
01:03Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
01:14Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
01:13Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...