Many Western songs are hierarchically structured in stanzas and phrases. The melody of the song is repeated for each stanza, while the lyrics vary. Each stanza is subdivided into phrases. It is to be expected that melodic and textual formulae at the end of the phrases offer intrinsic clues of closure to a listener or singer. In the current paper we aim at a method to detect such cadences in symbolically encoded folk songs. We take a trigram approach in which we classify trigrams of notes and pitches as cadential or as non-cadential. We use pitch, contour, rhythmic, textual, and contextual features, and a group of features based on the conditions of closure as stated by Narmour (1990). We employ a random forest classification algorithm. The precision of the classifier is considerably improved by taking the class labels of adjacent trigrams into account. An ablation study shows that none of the kinds of features is sufficient to account for good classification, while some of the groups perform moderately well on their own.
This paper presents both a method to detect cadences in Western folk-songs, particularly in folk songs from Dutch oral tradition, and a study to the importance of various musical parameters for cadence detection.
There are various reasons to focus specifically on cadence patterns. The concept of cadence has played a major role in the study of Western folk songs. In several of the most important folks song classification systems, cadence tones are among the primary features that are used to put the melodies into a linear ordering. In one of the earliest classification systems, devised by Ilmari Krohn (REF 1903), melodies are firstly ordered according to the number of phrases, and secondly according to the sequence of cadence tones. This method was adapted for Hungarian melodies by Bártok an