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Reliable Local Explanations for Machine Listening
(IEEE, 2020-07-19)
One way to analyse the behaviour of machine learning models is through local explanations that highlight input features that maximally influence model predictions. Sensitivity analysis, which involves analysing the effect ...
Adversarial Unsupervised Domain Adaptation for Harmonic-Percussive Source Separation
(Institute of Electrical and Electronics Engineers, 2020)
This paper addresses the problem of domain adaptation for the task of music source separation. Using datasets from two different domains, we compare the performance of a deep learning-based harmonic-percussive source ...
Pitch-informed instrument assignment using a deep convolutional network with multiple kernel shapes
(International Society for Music Information Retrieval, 2021-11-09)
This paper proposes a deep convolutional neural network for performing note-level instrument assignment. Given a polyphonic multi-instrumental music signal along with its ground truth or predicted notes, the objective is ...
Detecting cover songs with pitch class key-invariant networks
(IEEE, 2021-10-25)
Deep Learning (DL) has recently been applied successfully to the task of Cover Song Identification (CSI). Meanwhile, neural networks that consider music signal data structure in their design have been developed. In this ...
PiJAMA: Piano Jazz with Automatic MIDI Annotations
(Ubiquity Press, 2023)
Recent advances in automatic piano transcription have enabled large scale analysis of piano music in the symbolic domain. However, the research has largely focused on classical piano music. We present PiJAMA (Piano Jazz ...
A Data-Driven Analysis of Robust Automatic Piano Transcription
(Institute of Electrical and Electronics Engineers, 2024)
Algorithms for automatic piano transcription have improved dramatically in recent years due to new datasets and modeling techniques. Recent developments have focused primarily on adapting new neural network architectures, ...