Comparison of whole-word and phoneme scoring for SBMU-1 monosyllabic words in presence of speech-spectrum noise: A psychometric function study
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Abstract
Background and Aim: Speech audiometry assesses functional hearing beyond pure-tone thresholds, reflecting real-world speech perception. The present study compared whole-word and phoneme scoring methods for the Persian SBMU-1 monosyllabic word lists presented in speech-spectrum noise to determine their psychometric equivalence and sensitivity to signal-to-noise ratio (SNR) changes.
Methods: Twenty-two young adults with normal hearing participated. SBMU-1 consonant–vowel–consonant (CVC) words were presented binaurally at six SNRs (−5, 0, +5, +10, +15, +20 dB) in speech-spectrum noise at 60 dB HL. Recognition performance was analyzed using whole-word and phoneme scoring. List equivalency and scoring effects were examined using Friedman and Wilcoxon signed-rank tests with Bonferroni correction.
Results: Speech recognition improved systematically with increasing SNR for both scoring methods. Phoneme scoring consistently yielded higher scores than whole-word scoring, especially under low SNRs, revealing a 10–20% performance advantage. At high SNRs, the two methods converged. Across lists, differences were minor and list-specific, confirming the general equivalency of SBMU -1 lists in noise.
Conclusion: Phoneme scoring provides a more sensitive measure of perceptual performance in noise by capturing partial recognition, whereas whole-word scoring better represents functional communication ability. The SBMU-1 word lists are psychometrically balanced and suitable for both clinical and research applications in Persian speech audiometry.
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