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Pleasantness and Familiarity Predict Liking of Music Selected by the Armonique Music Search Engine

Faculty Supervisor:
Dwight Krehbiel
Year of Project Completion:
2009
Student:
Sonia Barrera

Abstract

Abstract of a poster presented at the Student Research Conference of Sigma Xi, The Woodlands, TX, Nov. 14,2009: Research has shown that familiarity is an important factor in liking of music. For example, Schubert (2007) found that familiarity and pleasantness predicted liking, albeit in a rather small set of familiar classical compositions. In the present study a more diverse sample of music was obtained by means of a music search engine (Manaris et al., 2008). Since a prior study in our laboratory showed that general familiarity ratings were a strong predictor of liking ratings (Burns & Pryce, 2009), we investigated whether ratings of pleasantness and activation may account for an additional portion of the variability in liking. For each participant, a song was chosen from one of the participant’s three favorite genres. The Armonique music search engine was used to find two similar and two dissimilar songs. In a similar manner, Armonique was also used to find another set of seven songs (original, three similar and three dissimilar) to which all participants listened. The forty participants in the study listened to the twelve musical excerpts in a random order, rating their liking, familiarity, pleasantness, and activation after each piece. By means of hierarchical linear modeling we found that familiarity and pleasantness together, but not activation, were each strong predictors of liking (p<0.001), in both sets of songs. Musical experience (years of music lessons) interacted significantly with pleasantness in predicting liking for the set of seven songs (p=0.015). The results extend previous findings to show that, across diverse music selections, liking may be influenced by familiarity and pleasantness, possibly moderated by musical experience.

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