Automatic transcription of Turkish microtonal music.

Automatic music transcription, a central topic in music signal analysis, is typically limited to equal-tempered music and evaluated on a quartertone tolerance level. A system is proposed to automatically transcribe microtonal and heterophonic music as applied to the makam music of Turkey. Specific traits of this music that deviate from properties targeted by current transcription tools are discussed, and a collection of instrumental and vocal recordings is compiled, along with aligned microtonal reference pitch annotations. An existing multi-pitch detection algorithm is adapted for transcribing music with 20 cent resolution, and a method for converting a multi-pitch heterophonic output into a single melodic line is proposed. Evaluation metrics for transcribing microtonal music are applied, which use various levels of tolerance for inaccuracies with respect to frequency and time. Results show that the system is able to transcribe microtonal instrumental music at 20 cent resolution with an F-measure of 56.7%, outperforming state-of-the-art methods for the same task. Case studies on transcribed recordings are provided, to demonstrate the shortcomings and the strengths of the proposed method.

Commonality and variation in mental representations of music revealed by a cross-cultural comparison of rhythm priors in 15 countries.

Music is present in every known society but varies from place to place. What, if anything, is universal to music cognition? We measured a signature of mental representations of rhythm in 39 participant groups in 15 countries, spanning urban societies and Indigenous populations. Listeners reproduced random 'seed' rhythms; their reproductions were fed back as the stimulus (as in the game of 'telephone'), such that their biases (the prior) could be estimated from the distribution of reproductions. Every tested group showed a sparse prior with peaks at integer-ratio rhythms. However, the importance of different integer ratios varied across groups, often reflecting local musical practices. Our results suggest a common feature of music cognition: discrete rhythm 'categories' at small-integer ratios. These discrete representations plausibly stabilize musical systems in the face of cultural transmission but interact with culture-specific traditions to yield the diversity that is evident when mental representations are probed across many cultures.

Relations between perceived affect and liking for melodies and visual designs.

Sensory valuation is a fundamental aspect of cognition. It involves assigning hedonic value to a stimulus based on its sensory information considering personal and contextual factors. Hedonic values (e.g., liking) can be deemed affective states that motivate behavior, but the relations between hedonic and affective judgments have yet to be established. To fill this gap, we investigated the relations between stimulus features, perceived affect, and liking across domains and with potentially relevant individual traits. Fifty-eight participants untrained in music and visual art rated their liking and perceived valence and arousal for visual designs and short melodies varying in balance, contour, symmetry, or complexity and filled out several questionnaires. First, we examined group-level relations between perceived affect and liking across domains. Second, we inspected the relations between the individual use of musical and visual properties in judgments of liking and perceived affect-that is, between aesthetic and perceived-affect sensitivities. Third, we inquired into the influence of information-related (need for cognition, or NFC) and affect-related (need for emotion) traits on individual sensitivities. We found domain-specific effects of the stimulus features on liking, a linear association between valence and liking, the inverted-U model of arousal and liking, a binary profile of musical aesthetic sensitivities, and a modulatory effect of NFC on how people use stimulus properties in their hedonic and affective judgments. In summary, the results suggest that hedonic value is primarily computed from domain-specific sensory information partially moderated by NFC. (PsycInfo Database Record (c) 2023 APA, all rights reserved).