8 accepted papers
Deep Learning (DL) is commonly used in music processing tasks such as Automatic Chord Recognition (ACR), for which Convolutional Neural Networks (CNNs) are popular tools. Compression of CNNs has become a research topic of interest, focused on post-pruning of learnt networks and development of less e…
Automatic Chord Recognition (ACR) seeks to extract chords from musical signals. Recently, deep neural network (DNN) approaches have become popular for this task, being employed for feature extraction and sequence modelling. Traditionally, the most important steps in ACR were extraction of chroma fea…
Onset detection is a fundamental task in musical signal processing, providing information for higher level applications. Different classes of onsets can be found in musical signals, determined as being hard, or soft, by the initial energy transfer. Most onset detectors are general purpose and attemp…
A major goal in blind source separation to identify and separate sources is to model their inherent characteristics. While most state-of-the-art approaches are supervised methods trained on large datasets, interest in non-data-driven approaches such as Kernel Additive Modelling (KAM) remains high du…
The task of chord recognition in music signals is often based upon pattern matching in chromagrams. Many variants of chroma exist and quality of chord recognition is related to the feature employed. Chroma Reduced Pitch (CRP) features are interesting in this context as they were designed to improve…
The estimation of rhythmic properties such as tempo, beat positions or metrical structure are central aspects of Music Information Retrieval (MIR) research. Meter inference algorithms are typically designed to track metrical structure in presence of mild deviations of the feature estimates over time…
Performance of Non-negative Matrix Factorisation (NMF) can be diminished when the underlying factors consist of elements that overlap in the matrix to be factorised. The use of ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> sparsity may impro…
Non-negative Matrix Factorisation (NMF) is a commonly used tool in many musical signal processing tasks, including Automatic Music Transcription (AMT). However unsupervised NMF is seen to be problematic in this context, and harmonically constrained variants of NMF have been proposed. While useful, t…