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Explaining the decisions of anomalous sound detectors
(2022-11-03)
Deciding whether a sound is anomalous is accomplished by comparing it to a learnt distribution of inliers. Therefore, learning a distribution close to the true population of inliers is vital for anomalous sound detection ...
Leveraging label hierarchies for few-shot everyday sound recognition
(2022-11-03)
Everyday sounds cover a considerable range of sound categories in our daily life, yet for certain sound categories it is hard to collect sufficient data. Although existing works have applied few-shot learning paradigms to ...
Contrastive audio-language learning for music
(ISMIR, 2022-12-04)
As one of the most intuitive interfaces known to humans, natural language has the potential to mediate many tasks that involve human-computer interaction, especially in application-focused fields like Music Information ...
Performance MIDI-to-score conversion by neural beat tracking
(2022-12-18)
Rhythm quantisation is an essential part of converting performance MIDI recordings into musical scores. Previous works on rhythm quantisation are limited to the use of probabilistic or statistical methods. In this paper, ...
Large-Scale Pretrained Model for Self-Supervised Music Audio Representation Learning
(2022-12-20)
Self-supervised learning technique is an under-explored topic for music audio due to the challenge of designing an appropriate training paradigm. We hence propose MAP-MERT, a large-scale music audio pre-trained model for ...
EnsembleSet: A new high-quality synthesised dataset for chamber ensemble separation
(2022-12-08)
Music source separation research has made great advances in recent years, especially towards the problem of separating vocals, drums, and bass stems from mastered songs. The advances in this field can be directly attributed ...