Development of an Afrikaans test for sentence recognition in noise

Abstract

Speech audiometry is considered an essential tool in the assessment of hearing, not only to validate pure tone measurements, but also to indicate speech perception as a critical communicative function. The use of sentence material in the assessment of speech perception has great value as it simulates – more closely than single words – the type of speech stimuli that listeners are confronted with on a daily basis. In South Africa, speech recognition (reception and discrimination) abilities are most commonly assessed through the use of single words, presented by monitored live voice, a practice sternly criticized in the literature. Furthermore, speech recognition is commonly evaluated in an ideal (quiet) listening environment. This method gives an incomplete impression of a patient’s auditory performance, since everyday listening situations are often characterised by the presence of background noise that influences comprehension of speech. The present study was therefore launched with the aim to develop a reliable measure of speech recognition in noise using Afrikaans sentence material. The development of the test was conducted in three phases. The first phase entailed the compilation of culturally valid, pre-recorded Afrikaans sentence material. During the second phase the uniformity of the recorded sentence collection was improved by determining the intelligibility of each sentence in the presence of noise and eliminating sentences that were not of equivalent difficulty in this regard. The objective of the third phase was to arrange the sentence material into lists using two different methods of list compilation. The first method involved grouping sentences together based solely on their intelligibility in noise (as assessed in the previous phase). The second method was the well-documented method of compiling phonetically balanced lists. The inter-list reliability of both sets of lists was evaluated in both normal hearing listeners and listeners with a simulated high frequency hearing loss. The results provided valuable information on the process of developing a test of speech recognition in noise, especially in terms of options for list compilation. Findings indicated that lists compiled according to intelligibility in noise showed a higher degree of equivalence than phonetically balanced lists when applied to normally hearing listeners. However, when applied to listeners with a simulated loss, phonetically balanced lists displayed greater equivalence. The developed test provides a means of assessing speech recognition in noise in Afrikaans, and shows potential for application in the assessment of hearing impaired populations, individuals with auditory processing difficulties, and the paediatric population. In addition, the methodology described for the development of the test could provide a valuable guideline for future researchers looking to develop similar tests in other languages.