Add like
Add dislike
Add to saved papers

Predicting Variation of Folk Songs: A Corpus Analysis Study on the Memorability of Melodies.

We present a hypothesis-driven study on the variation of melody phrases in a collection of Dutch folk songs. We investigate the variation of phrases within the folk songs through a pattern matching method which detects occurrences of these phrases within folk song variants, and ask the question: do the phrases which show less variation have different properties than those which do? We hypothesize that theories on melody recall may predict variation, and as such, investigate phrase length, the position and number of repetitions of a given phrase in the melody in which it occurs, as well as expectancy and motif repetivity. We show that all of these predictors account for the observed variation to a moderate degree, and that, as hypothesized, those phrases vary less which are rather short, contain highly expected melodic material, occur relatively early in the melody, and contain small pitch intervals. A large portion of the variance is left unexplained by the current model, however, which leads us to a discussion of future approaches to study memorability of melodies.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app