Title: Computational analyses of auditory discriminability using data from acceptable signal-to-noise ratio experiment

Authors: Bankole K. Fasanya

Addresses: Department of Construction Science and Organizational Leadership, Environmental Health and Safety, Purdue University Northwest, Hammond, IN 46323, USA

Abstract: The current research gap in the area of human auditory performances inspired the need to develop a mathematical model that establishes the relationship between auditory sound discriminability (d'), sound familiarity (k), signal-to-noise ratio (SNR) and acceptable signal-to-noise ratio (ASNR). This paper developed the mathematical models that showed the relationship between k, d', SNR and ASNR. ASNR archival data from 20 students at a public university located in the eastern region of the USA was used to validate the models. Participants' ages ranged from 23 to 35 years old. Findings from the model simulations revealed a threshold familiarity score (q*), the point at which k and SNR assumed the same value. ANOVA result showed (p < 0.0001), which indicated a statistically significant effect of ASNR and sound familiarity (k) on d' with R² = 94%. The findings were applicable to auditory detection task only.

Keywords: signal-to-noise ratio; SNR; auditory discriminability; d'; acceptable signal-to-noise ratio; ASNR; sound familiarity; k; threshold familiarity score; q*.

DOI: 10.1504/IJHFE.2019.102301

International Journal of Human Factors and Ergonomics, 2019 Vol.6 No.2, pp.143 - 159

Received: 16 Nov 2018
Accepted: 19 Apr 2019
Published online: 16 Sep 2019 *

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