Melodic similarity among folk songs: An annotation study on similarity-based categorization in music

Abstract

In this article we determine the role of different musical features for the human categorization of folk songs into tune families in a large collection of Dutch folk songs. Through an annotation study we investigate the relation between musical features, perceived similarity and human categorization in music. We introduce a newly developed annotation method which is used to create an annotation data set for 360 folk song melodies in 26 tune families. This dataset delivers valuable information on the contribution of musical features to the process of categorization which is based on assessing the similarity between melodies. The analysis of the annotation data set reveals that the importance of single musical features for assessing similarity varies both between and within tune families. In general, the recurrence of short characteristic motifs is most relevant for the perception of similarity between songs belonging to the same tune family. Global melodic features often used for the description of melodies (such as melodic contour) play a less important role. The annotation data set is a valuable resource for further research on melodic similarity and can be used as enriched 'ground truth' to test various kinds of retrieval algorithms in Music Information Retrieval. Our annotation study exemplifies that assessing similarity is crucial for human categorization processes, which has been questioned within Cognitive Science in the context of rule-based approaches to categorization.2

Melodic Similarity and Applications Using Biologically-Inspired Techniques

“…Specifically when it comes to classifying folk songs into tune families, i.e., groups of songs with a common ancestor, Cowdery [68] considers the shared patterns to be a key criterion. An annotation study on Dutch folk songs by Volk and Van Kranenuburg [4] also supported this claim by proving that shared, stable musical patterns, called motifs were important for the expert assessment of music similarity. Consequently, we can theoretically use the motif alignment as reference for evaluating the quality of musical sequence alignment.…”

Documenting a song culture: the Dutch Song Database as a resource for musicological research

“…Experts make intuitive and holistic decisions without an explicated system about rules of categorization that determines how musical features may contribute to a given similarity assessment. We have therefore developed an annotation study to explicate the features that play a role in the categorization of similar melodies in tune families [31]. The motivation for the annotation study came from the goal of the WITCHCRAFT-project-to develop a search engine for the folk songs that will allow researchers and laymen to automatically find similar melodies.…”

“…Melodies of Onder de groene linde are classified into tune families, each family consisting of a set of similar melodies. According to an annotation study that was carried out to reveal the role of several musical features in creating perceptions of similarity between melodies [31], the most important ingredient of perceived melodic similarity appeared to be the occurrence of similar motifs between songs belonging to the same tune family. Therefore, the collection of the songs, together with the annotated motifs as distributed in the data set MTC-ANN, provides an invaluable resource within the field of automatic pattern discovery in Computational Music Analysis, and for the investigations into the role of repetition in music.…”

“…According to musicologists, repetition is an essential feature of music [5], which occurs on all levels of musical organization [18], existing both within a given musical work and between musical works. Yet, there are many open questions with regard to the specifics of repetition in musical works and styles [31], such as the question as to whether some composers employ repetition more than others [18].…”

Aspects of Tempo and Rhythmic Elaboration in Hindustani Music: A Corpus Study

“…In a corpus study of Ethiopian lyre, Conklin et al (2015) refined the methods further to work when no specific anti-corpus is available that helps to define what a pattern of interest could be. Volk and van Kranenburg (2012) determined melodic features that were used to classify Dutch folk songs into tune families. To this end, a subset of a corpus with 2,500 song transcriptions was used, and experts were asked to rate melody pairs in terms of similarity regarding melodic contour, rhythm, and other aspects.…”