Development of the Continuous Number Identification Test (CNIT): feasibility of dynamic assessment of speech intelligibility.

Objective: The present study was motivated by a need for a speech intelligibility test capable of indexing dynamic changes in the environment and adaptive processing in hearing aids. The Continuous Number Identification Test (CNIT) was developed to meet these aims. Design: From one location in the f...

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Detalles Bibliográficos
Publicado en:International Journal of Audiology Vol. 59; no. 6; pp. 434 - 443
Autores principales: Ozmeral, Erol J., Hoover, Eric C., Gabbidon, Patricia, Eddins, David A.
Formato: equations & formulas research tables/charts Journal Article
Publicado: Taylor & Francis Ltd Jun2020
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:Objective: The present study was motivated by a need for a speech intelligibility test capable of indexing dynamic changes in the environment and adaptive processing in hearing aids. The Continuous Number Identification Test (CNIT) was developed to meet these aims. Design: From one location in the free field, speech was presented in noise (∼2 words/s) with a 100-ms inter-word interval. On average, every fourth word was a target digit and all other words were monosyllabic words. Non-numeric words had a fixed presentation level such that the dominant signal-to-noise-ratio (SNR) was held at +6 dB SNR relative to background maskers. To prevent ceiling effects, however, targets were presented at a user-specific SNR, determined by an initial adaptive-tracking procedure that estimated the 79.4% speech reception threshold. Study sample: Ten normal-hearing listeners participated. Results: The CNIT showed comparable psychometric qualities of other established speech tests for long time scales (Exp. 1). Target-location changes did not affect performance on the CNIT (Exp. 2), but the test did show high temporal resolution in assessing sudden changes to SNR (Exp. 3). Conclusions: The CNIT is highly customisable, and the initial experiments tested feasibility of its primary features which set it apart from currently available speech-in-noise tests.