Music genre classification is one of the sub-disciplines of music information retrieval (MIR)
with growing popularity among researchers, mainly due to the already open challenges …

Instrument activity detection is a fundamental task in music information retrieval, serving as a
basis for many applications, such as music recommendation, music tagging, or remixing …

Characterising Confounding Effects in Music Classification Experiments through Interventions
Page 1 http://www.diva-portal.org This is the published version of a paper published in …

While there is a consensus that evaluation practices in music informatics (MIR) must be
improved, there is no consensus about what should be prioritised in order to do so. Priorities …

This dissertation addresses audio classification by designing signal representations which
satisfy appropriate invariants while preserving inter-class variability. First, we study time …

Deep neural networks have frequently been used to directly learn representations useful for
a given task from raw input data. In terms of overall performance metrics, machine learning …

Validity is the truth of an inference made from evidence, such as data collected in an
experiment, and is central to working scientifically. Given the maturity of the domain of music …

Deep neural networks (DNNs) are successfully applied in a wide variety of music
information retrieval (MIR) tasks. Such models are usually considered" black boxes" …

Validity is the truth of an inference made from evidence and is a central concern in scientific
work. Given the maturity of the domain of music information research (MIR), validity in our …

Composers of music can express emotions and communicate with their audience in a
multitude of ways. They decide on which voices or instruments to use, arrange notes into …