Listeners can attend to and track instruments or singing voices in complex musical mixtures, even though the acoustical energy of sounds from individual instruments may overlap in time and frequency. In popular music, lead vocals are often accompanied by sound mixtures from a variety of instruments, such as drums, bass, keyboards, and guitars. However, little is known about how the perceptual organization of such musical scenes is affected by selective attention, and which acoustic features play the most important role. To investigate these questions, we explored the role of auditory attention in a realistic musical scenario. We conducted three online experiments in which participants detected single cued instruments or voices in multi-track musical mixtures. Stimuli consisted of 2-s multi-track excerpts of popular music. In one condition, the target cue preceded the mixture, allowing listeners to selectively attend to the target. In another condition, the target was presented after the mixture, requiring a more “global” mode of listening. Performance differences between these two conditions were interpreted as effects of selective attention. In Experiment 1, results showed that detection performance was generally dependent on the target’s instrument category, but listeners were more accurate when the target was presented prior to the mixture rather than the opposite. Lead vocals appeared to be nearly unaffected by this change in presentation order and achieved the highest accuracy compared with the other instruments, which suggested a particular salience of vocal signals in musical mixtures. In Experiment 2, filtering was used to avoid potential spectral masking of target sounds. Although detection accuracy increased for all instruments, a similar pattern of results was observed regarding the instrument-specific differences between presentation orders. In Experiment 3, adjusting the sound level differences between the targets reduced the effect of presentation order, but did not affect the differences between instruments. While both acoustic manipulations facilitated the detection of targets, vocal signals remained particularly salient, which suggest that the manipulated features did not contribute to vocal salience. These findings demonstrate that lead vocals serve as robust attractor points of auditory attention regardless of the manipulation of low-level acoustical cues.
Auditory scene analysis (ASA) is the process by which the auditory system makes sense of complex acoustic environments through organizing sound mixtures into meaningful events and streams. Although music psychology has acknowledged the fundamental role of ASA in shaping music perception, no efficient test to quantify listeners’ ASA abilities in realistic musical scenarios has been published yet. This study presents a new tool for testing ASA abilities in the context of music, suitable for both normal-hearing (NH) as well as hearing-impaired (HI) individuals: The adaptive Musical Scene Analysis (MSA) test. The test uses a simple ‘yes-no’ task paradigm to determine if the sound from a single target instrument is heard in a mixture of popular music. During the online calibration phase, 525 NH and 131 HI listeners were recruited. The level-ratio between the target instrument and the mixture, choice of target instrument, and number of instruments in the mixture were found to be important factors affecting item difficulty, whereas the influence of the stereo width only had a minor effect. Based on Bayesian logistic mixed effects model, an adaptive version of the MSA test was developed. In a subsequent validation experiment with 74 listeners (20 HI), MSA scores showed acceptable test-retest reliability and moderate correlations with other music-related tests, pure-tone-average audiograms, age, musical sophistication, and working memory capacities. The MSA test is a user-friendly and efficient open-source tool for evaluating musical ASA abilities and is suitable for profiling the effects of hearing impairment on music perception.
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