ORIGINAL ARTICLE
COMPARISON OF PSYCHOACOUSTIC MEASURES USING TWO PIECES OF SOFTWARE: PSYCON AND MATLAB’S MAXIMUM LIKELIHOOD PROCEDURE
Sandeep Kumar 1, B-E
,
 
,
 
,
 
Kishore Tanniru 2, A,D-F
,
 
Chandni Jain 1, A,C-F
 
 
 
More details
Hide details
1
Audiology, All India Institute of Speech and Hearing, India
 
2
Rehabilitative Health Sciences,, College of Applied Medical sciences, KSU, Riyadh - 11433., Saudi Arabia
 
 
A - Research concept and design; B - Collection and/or assembly of data; C - Data analysis and interpretation; D - Writing the article; E - Critical revision of the article; F - Final approval of article;
 
 
Submission date: 2022-02-10
 
 
Final revision date: 2022-03-23
 
 
Acceptance date: 2022-05-13
 
 
Publication date: 2022-06-30
 
 
Corresponding author
Chandni Jain   

Audiology, All India Institute of Speech and Hearing, Naimisham Campus, 570006, Mysuru, India
 
 
J Hear Sci 2022;12(2):44-48
 
KEYWORDS
TOPICS
ABSTRACT
Background:
Psychoacoustic abilities play a crucial role in speech perception. Psycon and Matlab’s maximum likelihood procedure (MLP) are two commonly used pieces of software to assess psychoacoustic ability. The present work compares a number of psychoacoustic abilities based on Psycon and MLP.

Material and methods:
There were 39 participants with normal hearing sensitivity who were enrolled in this study. The psychoacoustic measures assessed were gap detection threshold (GDT), duration discrimination threshold (DDT), difference limen of intensity (DLI), and difference limen of frequency (DLF). These measures were done using both Psycon and MLP, and a comparison was made between the two. An attempt was made to keep the stimuli specifications similar in Psycon and MLP except for the duration of stimuli in GDT.

Results:
A Wilcoxon signed-rank test was used to determine the significance of differences between MLP and Psycon. The results showed no significant difference in DLI, DLF, and DDT between MLP and Psycon; however, a significant difference was found in GDT.

Conclusions:
It can be concluded that the results of DLI, DLF, and DDT can be generalized between Psycon and MLP. However, further research with a larger sample would strengthen the current study’s findings.

REFERENCES (13)
1.
Ballou G. Handbook for Sound Engineers (Fourth ed.). Burlington: Focal Press, 2008; p. 43.
 
2.
Dreschler WA, Plomp R. Relation between psychophysical data and speech perception for hearing‐impaired subjects. I. J Acoust Soc Am, 1980; 68(6): 1608–15.
 
3.
Glasberg BR, Moore BCJ. Psychoacoustic abilities of subjects with unilateral and bilateral cochlear hearing impairments and their relationship to the ability to understand speech. Scand Audiol Suppl, 1989; 18(32): 3–25.
 
4.
Jain C, Devi N, Parthasarathy S, Kavitha S. Effect of musical training on psychophysical abilities and working memory in children. J Indian Speech Lang Hear Assoc, 2019; 33(2): 71–4.
 
5.
Devi N, Amritha G, Tanniru K. Effects of nonlinear amplification on differential sensitivity measures in individuals with cochlear hearing impairment. Indian J Otol, 2017; 23(3): 162–7.
 
6.
Alhaidary AA, Tanniru K, Aljadaan AF, Alabdulkarim LM. Auditory temporal resolution in adaptive tasks: gap detection investigation. Saudi Med J, 2019; 40(1): 52–8.
 
7.
Jain C, Joshi K. Test–retest reliability of various psychoacoustic measures using the maximum likelihood procedure. J Hear Sci, 2020;10(2): 55–9.
 
8.
Alhaidary A, Tanniru K. Across- and within-channel gap detection thresholds yielded by two different test applications. J Am Acad Audiol, 2020; 31(2): 111–7.
 
9.
Grassi M, Soranzo A. MLP: a MATLAB toolbox for rapid and reliable auditory threshold estimation. Behav Res Methods, 2009; 41(1): 20–8.
 
10.
Kwon BJ. AUX: a scripting language for auditory signal processing and software packages for psychoacoustic experiments and education. Behav Res Methods, 2012; 44(2): 361–73.
 
11.
Levitt H. Transformed up–down methods in psychoacoustics. J Acoust Soc Am, 1971; 49: 467–77.
 
12.
Ahmed WK. Advantages and disadvantages of using MATLAB/ode45 for solving differential equations in engineering applications. Intl J Eng, 2013; 7(1): 25–31.
 
13.
Schneider BA, Hamstra SJ. Gap detection thresholds as a function of tonal duration for younger and older listeners. J Acoust Soc Am, 1999; 106(1): 371–80.
 
Journals System - logo
Scroll to top