11/29/2022 0 Comments Polyphonic music examplesRepresentation learning for application to music has become an increasingly active field of research in recent years, as Figure 1 demonstrates. Using a known algorithm, by simply augmenting the training set with the JS Fake State-of-the-art validation set loss for the canonical JSB Chorales dataset, Finally, we conductĪblation studies to demonstrate the effectiveness of using the synthetic piecesįor research in polyphonic music modelling, and find that we can improve on They took to submit their response for each sample. With the MIDI samples, such as the respondents' musical experience and how long Human evaluation, designed to be as fair to the listener as possible, and findĭistinguishing JS Fake Chorales from real chorales composed by JS Bach.įurthermore, we make anonymised data collected from experiments available along We take consecutive outputsįrom the algorithm and avoid cherry-picking in order to validate the potential Learning-based algorithm, provided in MIDI form. We propose the JS Fake Chorales, a dataset of 500 pieces generated by a new Metrics correlating strongly with qualitative success remain elusive. Relevant to the generative modelling problem-space, where clear objective The issue of scale persists as a general hindrance towardsīreakthroughs in the field, while the lack of listener evaluation is especially In particular, datasets whichĬontain information revealing insights about human responses to the given music Language modelling or image classification. Music remain less readily-accessible at scale than in other domains, such as High quality datasets for learning-based modelling of polyphonic symbolic
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