A Matrixed Speech-in-Noise Test to Discriminate Favorable Listening Conditions by Means of Intelligibility and Response Time Results.

Research paper by Chiara C Visentin, Nicola N Prodi

Indexed on: 31 May '18Published on: 31 May '18Published in: Journal of speech, language, and hearing research : JSLHR


The primary aim of this study was to develop and examine the potentials of a new speech-in-noise test in discriminating the favorable listening conditions targeted in the acoustical design of communication spaces. The test is based on the recognition and recall of disyllabic word sequences. A secondary aim was to compare the test with current speech-in-noise tests, assessing its benefits and limitations. Young adults (19-40 years old), self-reporting normal hearing, were presented with the newly developed Words Sequence Test (WST; 16 participants, Experiment 1) and with a consonant confusion test and a sentence recognition test (Experiment 2, 36 participants randomly assigned to the 2 tests). Participants performing the WST were presented with word sequences of different lengths (from 2 up to 6 words). Two listening conditions were selected: (a) no noise and no reverberation, and (b) reverberant, steady-state noise (Speech Transmission Index: 0.47). The tests were presented in a closed-set format; data on the number of words correctly recognized (speech intelligibility, IS) and the response times (RTs) were collected (onset RT, single words' RT). It was found that a sequence composed of 4 disyllabic words ensured both the full recognition score in quiet conditions and a significant decrease in IS results when noise and reverberation degraded the speech signal. RTs increased with the worsening of the listening conditions and the number of words of the sequence. The greatest onset RT variation was found when using a sequence of 4 words. In the comparison with current speech-in-noise tests, it was found that the WST maximized the IS difference between the selected listening conditions as well as the RT increase. Overall, the results suggest that the new speech-in-noise test has good potentials in discriminating conditions with near-ceiling accuracy. As compared with current speech-in-noise tests, it appears that the WST with a 4-word sequence allows for a finer mapping of the acoustical design target conditions of public spaces through accuracy and onset RT data.