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arXiv · 1903.08756

Distributed Vector Representations of Folksong Motifs

Aitor Arronte-Alvarez·Francisco Gómez-Martin
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Abstract

This article presents a distributed vector representation model for learning folksong motifs. A skip-gram version of word2vec with negative sampling is used to represent high quality embeddings. Motifs from the Essen Folksong collection are compared based on their cosine similarity. A new evaluation method for testing the quality of the embeddings based on a melodic similarity task is presented to show how the vector space can represent complex contextual features, and how it can be utilized for the study of folksong variation.

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Aitor Arronte-Alvarez, Francisco Gómez-Martin. 2019-03-20. Distributed Vector Representations of Folksong Motifs. https://arxiv.org/abs/1903.08756

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