The increasing number of casting shows and talent contests in the media over the past years suggests a public interest in rating the quality of vocal performances. In many of these formats, laymen alongside music experts act as judges. Whereas experts' judgments are considered objective and reliable when it comes to evaluating singing voice, little is known about laymen's ability to evaluate peers. On the one hand, layman listeners–who by definition did not have any formal training or regular musical practice–are known to have internalized the musical rules on which singing accuracy is based. On the other hand, layman listeners' judgment of their own vocal skills is highly inaccurate. Also, when compared with that of music experts, their level of competence in pitch perception has proven limited. The present study investigates laypersons' ability to objectively evaluate melodies performed by untrained singers. For this purpose, laymen listeners were asked to judge sung melodies. The results were compared with those of music experts who had performed the same task in a previous study. Interestingly, the findings show a high objectivity and reliability in layman listeners. Whereas both the laymen's and experts' definition of pitch accuracy overlap, differences regarding the musical criteria employed in the rating task were evident. The findings suggest that the effect of expertise is circumscribed and limited and supports the view that laypersons make trustworthy judges when evaluating the pitch accuracy of untrained singers.
Music, like language, is characterized by hierarchically organized structure that unfolds over time. Music listening therefore requires not only the tracking of notes and beats but also internally constructing high-level musical structures or phrases and anticipating incoming contents. Unlike for language, mechanistic evidence for online musical segmentation and prediction at a structural level is sparse. We recorded neurophysiological data from participants listening to music in its original forms as well as in manipulated versions with locally or globally reversed harmonic structures. We discovered a low-frequency neural component that modulated the neural rhythms of beat tracking and reliably parsed musical phrases. We next identified phrasal phase precession, suggesting that listeners established structural predictions from ongoing listening experience to track phrasal boundaries. The data point to brain mechanisms that listeners use to segment continuous music at the phrasal level and to predict abstract structural features of music.