2 papers
cs.SD2024
Similar but Faster: Manipulation of Tempo in Music Audio Embeddings for Tempo Prediction and Search
Matthew C. McCallum, Florian Henkel, Jaehun Kim +2
Audio embeddings enable large scale comparisons of the similarity of audio files for applications such as search and recommendation. Due to the subjectivity of audio similarity, it…
cs.SD2024
On the Effect of Data-Augmentation on Local Embedding Properties in the Contrastive Learning of Music Audio Representations
Matthew C. McCallum, Matthew E. P. Davies, Florian Henkel +2
Audio embeddings are crucial tools in understanding large catalogs of music. Typically embeddings are evaluated on the basis of the performance they provide in a wide range of down…