LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Melodic patterns and tonal cadences: Bayesian learning of cadential categories from contrapuntal information

Photo from academic.microsoft.com

ABSTRACT Recent work has shown that authentic and half cadences can be identified via harmonic features in both supervised and unsupervised settings, suggesting that humans may use such cues in… Click to show full abstract

ABSTRACT Recent work has shown that authentic and half cadences can be identified via harmonic features in both supervised and unsupervised settings, suggesting that humans may use such cues in perceiving and learning cadences. The present study tests melodic features in these same tasks. Both n-gram models and profile hidden Markov models of melodic patterns are used for supervised classification and unsupervised learning of cadences in Classical string quartets. Success is achieved at the supervised task but not the unsupervised task, indicating that melodic cues would help in perceiving cadences but not in learning to perceive them.

Keywords: learning cadential; patterns tonal; tonal cadences; cadences bayesian; melodic patterns; bayesian learning

Journal Title: Journal of New Music Research
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.