The Effect of Root-Mean-Square and Loudness-Based Calibration Approach on the Acceptable Noise Level

environment contains many background noises in everyday conversations, it is necessary to evaluate the noise tolerance. The Acceptable Noise Level (ANL) provides an approach to quantifying the maximum amount of background noise a listener is willing to put up with while listening to a target story without becoming tense. Exploring noise tolerance in speech perception, the study investigates how different calibration methods impact normal hearing participants’ monotic and dichotic ANL results. Methods: This investigation utilizes a pared-sample t-test for statistical analysis, adopting a comparative observational approach. This study applied the Persian version of the typical ANL test. Two approaches have equalized the target and background stimuli: Root Mean Squared (RMS) and loudness match calibration via Adobe Audition. Using these modified materials the Most Comfortable Level (MCL), the Background Noise Level (BNL), and ANL were compared in terms of RMS and loudness match calibration. Fifty normal persons aged (18–39), under the conditions of monotic and dichotic listening, participated in this study. Results: The statistical analysis using a paired-sample t-test revealed no significant differences in the outcomes of the ANL test between the calibrations of RMS and loudness matching under both monotic and dichotic listening conditions (p=0.31 and p=0.67, respectively). Conclusion: The study suggests that calibration procedures, namely RMS and Loudness matching, do not affect ANL in either monotic or dichotic conditions. Keywords: Loudness; calibration; acceptable noise level; root mean square

Authors

Institutions

Publication Details

Journal
Shinavāyī/shināsī./Shinavāyī/shināsī
Published
2024-10-13
DOI
https://doi.org/10.18502/avr.v33i4.16654
Citations
1
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
0.26
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Effect of Root-Mean-Square and Loudness-Based Calibration Approach on the Acceptable Noise Level

Raha Nekoutabar, Hamid Jalilvand, Fatemeh Sadat Ghaheri
1 citations
Shinavāyī/shināsī./Shinavāyī/shināsī
Structural Health Monitoring Techniques
0.26
article

The Effect of Root-Mean-Square and Loudness-Based Calibration Approach on the Acceptable Noise Level

Raha Nekoutabar, Hamid Jalilvand, Fatemeh Sadat Ghaheri
article en
1 citations

Abstract

environment contains many background noises in everyday conversations, it is necessary to evaluate the noise tolerance. The Acceptable Noise Level (ANL) provides an approach to quantifying the maximum amount of background noise a listener is willing to put up with while listening to a target story without becoming tense. Exploring noise tolerance in speech perception, the study investigates how different calibration methods impact normal hearing participants’ monotic and dichotic ANL results. Methods: This investigation utilizes a pared-sample t-test for statistical analysis, adopting a comparative observational approach. This study applied the Persian version of the typical ANL test. Two approaches have equalized the target and background stimuli: Root Mean Squared (RMS) and loudness match calibration via Adobe Audition. Using these modified materials the Most Comfortable Level (MCL), the Background Noise Level (BNL), and ANL were compared in terms of RMS and loudness match calibration. Fifty normal persons aged (18–39), under the conditions of monotic and dichotic listening, participated in this study. Results: The statistical analysis using a paired-sample t-test revealed no significant differences in the outcomes of the ANL test between the calibrations of RMS and loudness matching under both monotic and dichotic listening conditions (p=0.31 and p=0.67, respectively). Conclusion: The study suggests that calibration procedures, namely RMS and Loudness matching, do not affect ANL in either monotic or dichotic conditions. Keywords: Loudness; calibration; acceptable noise level; root mean square

Shinavāyī/shināsī./Shinavāyī/shināsī
Institute for Cognitive Science Studies (IR), Shahid Beheshti University of Medical Sciences (IR)
Openalex Percentile: Top 44%
Structural Health Monitoring Techniques
0.26
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.