Development of 20-Talker Korean Sentence In Noise Test Lists

Abstract

Purpose: Clinical speech recognition measures often present the sentences recorded with a single speaker and one rate of speech. Performances with single-talker recordings may not accurately represent the speech recognition abilities of the listeners in a multitalker communication situation. The present study aimed to construct and optimize the sentences recorded by 20 different talkers for sentence-in-noise recognition tests (20-talker Korean sentence-in-noise test, 20-talker K-SIN).Methods: Phases I and II were conducted in this study. In phase I (developmental phase), preliminary 720 sentences composed of 3 to 6 words were selected and recorded by twenty different talkers (10 male and 10 female). The recorded sentences were superimposed to generate a speech-shaped noise similar to the long-term average speech spectrum of the sentences. In phase II (optimization and formation of equally intelligible sentence lists), the psychometric functions of 30 normal-hearing listeners were obtained from the sentence-in-noise recognition scores at three different signal-to-noise ratios (SNRs) (-2, -4, and -7 dB). Based on these scores, the SNR required for 50% sentence intelligibility (SNR-50) and the slope at that point were derived from the psychometric function curves.Results: Before level adjustment, the median SNR-50 and slope were -4.12 dB SNR and 24.33%/dB over 720 sentences. Level adjustments were applied to homogenize the intelligibility of the sentences, resulting in 508 sentences remained. Out of 508 sentences, 320 sentences were used to construct 1 practice list and 15 test lists, wherein 20 sentences in each list were spoken by each of the 20 different talkers.Conclusion: The 20-talker K-SIN sentences can be used for high-variability speech-in-noise recognition test to better reflect the multitalker communication abilities of listeners.