Cadence Detection in Western Traditional Stanzaic Songs using Melodic and Textual Features

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 formulas 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 [11]. 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.