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Found 5 papers, 1 papers with code
Similar but Faster: Manipulation of Tempo in Music Audio Embeddings for Tempo Prediction and Search
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.
Tempo estimation as fully self-supervised binary classification
This paper addresses the problem of global tempo estimation in musical audio.
On the Effect of Data-Augmentation on Local Embedding Properties in the Contrastive Learning of Music Audio Representations
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.
Supervised and Unsupervised Learning of Audio Representations for Music Understanding
We find that restricting the domain of the pre-training dataset to music allows for training with smaller batch sizes while achieving state-of-the-art in unsupervised learning -- and in some cases, supervised learning -- for music understanding.
Unsupervised Learning of Deep Features for Music Segmentation
The performance of a range of music segmentation algorithms has been shown to be dependent on the audio features chosen to represent the audio.
