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A Study on the Transferability of Adversarial Attacks in Sound Event Classification
(IEEE, 2020-05-04)
An adversarial attack is an algorithm that perturbs the input of a machine learning model in an intelligent way in order to change the output of the model. An important property of adversarial attacks is transferability. ...
Robustness of Adversarial Attacks in Sound Event Classification
(2019-10-25)
An adversarial attack is a method to generate perturbations to the input of a machine learning model in order to make the output of the model incorrect. The perturbed inputs are known as adversarial examples. In this paper, ...
Violinist identification based on vibrato features
(EURASIP, 2021-08-23)
Identifying performers from polyphonic music is a challenging task in music information retrieval. As a ubiquitous expressive element in violin music, vibrato contains important information about the performers' interpretation. ...
Vocal Harmony Separation using Time-domain Neural Networks
(2021-08-30)
Polyphonic vocal recordings are an inherently challenging source separation task due to the melodic structure of the vocal parts and unique timbre of its constituents. In this work, we utilise a time-domain neural network ...
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 ...
Leveraging synthetic data for improving chamber ensemble separation
(IEEE, 2023-10-22)
In this work, we tackle the challenging problem of separating monophonic instrument mixtures found in chamber music from monaural recordings. This task differs from the Music Demixing Challenge where the task is to separate ...