Musicians’ speech-in-speech perception by age (Cohn et al., 2023)
Purpose: This study investigates the debate that musicians have an advantage in speech-in-noise perception from years of targeted auditory training. We also consider the effect of age on any such advantage, comparing musicians and nonmusicians (age range: 18–66 years), all of whom had normal hearing. We manipulate the degree of fundamental frequency (fo) separation between the competing talkers, as well as use different tasks, to probe attentional differences that might shape a musician’s advantage across ages.
Method: Participants (ranging in age from 18 to 66 years) included 29 musicians and 26 nonmusicians. They completed two tasks varying in attentional demands: (a) a selective attention task where listeners identify the target sentence presented with a one-talker interferer (Experiment 1), and (b) a divided attention task where listeners hear two vowels played simultaneously and identify both competing vowels (Experiment 2). In both paradigms, fo separation was manipulated between the two voices (Δfo = 0, 0.156, 0.306, 1, 2, 3 semitones).
Results: Results show that increasing differences in fo separation lead to higher accuracy on both tasks. Additionally, we find evidence for a musician’s advantage across the two studies. In the sentence identification task, younger adult musicians show higher accuracy overall, as well as a stronger reliance on fo separation. Yet, this advantage declines with musicians’ age. In the double vowel identification task, musicians of all ages show an across-the-board advantage in detecting two vowels—and use fo separation more to aid in stream separation—but show no consistent difference in double vowel identification.
Conclusions: Overall, we find support for a hybrid auditory encoding-attention account of music-to-speech transfer: The musician’s advantage includes fo, but the benefit also depends on the attentional demands in the task and listeners’ age. Taken together, this study suggests a complex relationship between age, musical experience, and speech-in-speech paradigm on a musician’s advantage.
Supplemental Material S1. Summary of musician’s advantage for speech-in-speech.
Supplemental Material S2. Calculations of semitone separation based on Kishon-Rabin et al. (2001).
Supplemental Material S3. Sentence identification (Experiment 1): Posterior means (Estimate), standard deviation of the posterior (Error), 95% credible intervals (Q2.5, Q97.5), and percent of posterior distribution above or below zero, for fixed effects. Effects whose credible intervals do not include zero, or those with 95% of their distribution on one side of 0 are in bold.
Supplemental Material S4. Confusion matrix for participants who did not reach 90% in single vowel identification (shown in percentages).
Supplemental Material S5. Confusion matrix for YA non-musicians who did reach 90% in single vowel identification (shown in percentages).
Supplemental Material S6. Confusion matrix for YA musicians who did reach 90% in single vowel identification (shown in percentages).
Supplemental Material S7. Confusion matrix for OA non-musicians who did reach 90% in single vowel identification (shown in percentages).
Supplemental Material S8. Confusion matrix for OA musicians who did reach 90% in single vowel identification (shown in percentages).
Supplemental Material S9. Double vowel identification (Experiment 2): Posterior means (Estimate), standard deviation of the posterior (Error), 95% credible intervals (Q2.5, Q97.5), and percent of posterior distribution above or below zero, for fixed effects. Effects whose credible intervals do not include zero, or those with 95% of their distribution on one side of 0 are in bold.
Cohn, M., Barreda, S., & Zellou, G. (2023). Differences in a musician’s advantage for speech-in-speech perception based on age and task. Journal of Speech, Language, and Hearing Research, 66(2), 545–564. https://doi.org/10.1044/2022_JSLHR-22-00259
