The objective of pattern-matching topics is to gain insights into repetitive patterns within or across various music genres and cultures. This approach aims to shed light on the recurring instances present in diverse musical traditions. The paper presents a study analyzing folk songs using symbolic music representation, including melodic sequences and musical information. By examining a corpus of 400 monophonic Slovenian tunes, we are releasing annotations of structure, contour, and implied harmony. We propose an efficient algorithm based on suffix arrays and bit-vectors to match both music content (melodic sequence) and context (descriptors). Our study reveals that certain descriptors, such as contour types and harmonic “stability” exhibit variations based on phrase position within a tune. Additionally, combining melody and descriptors in pattern-matching queries enhances precision for classification tasks. We emphasize the importance of the interplay between melodic sequences and music descriptors, highlighting that different pattern queries may have varying levels of detail requirements. As a result, our approach promotes flexibility in computational music analysis. Lastly, our objective is to foster the knowledge of Slovenian folk songs.

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