Similar but Faster: Manipulation of Tempo in Music Audio Embeddings for Tempo Prediction and Search

no code implementations • 17 Jan 2024 • Matthew C. McCallum, Florian Henkel, Jaehun Kim, Samuel E. Sandberg, Matthew E. P. Davies

We propose tempo translation functions that allow for efficient manipulation of tempo within a pre-existing embedding space whilst maintaining other properties such as genre.

Data Augmentation Retrieval +1

Tempo estimation as fully self-supervised binary classification

no code implementations • 17 Jan 2024 • Florian Henkel, Jaehun Kim, Matthew C. McCallum, Samuel E. Sandberg, Matthew E. P. Davies

This paper addresses the problem of global tempo estimation in musical audio.

Binary Classification Classification

On the Effect of Data-Augmentation on Local Embedding Properties in the Contrastive Learning of Music Audio Representations

no code implementations • 17 Jan 2024 • Matthew C. McCallum, Matthew E. P. Davies, Florian Henkel, Jaehun Kim, Samuel E. Sandberg

Similarly, we show that the optimal selection of data augmentation strategies for contrastive learning of music audio embeddings is dependent on the downstream task, highlighting this as an important embedding design decision.

Contrastive Learning Data Augmentation