Rhythm is a fundamental aspect of music and metrical structure is an important rhythm-related element. Several mid-level features encoding metrical structure information have been proposed in the literature, although the explicit extraction of this information is rarely considered. In this paper, we present a method to extract the full metrical structure from music recordings without the need for any prior knowledge. The algorithm is evaluated against expert annotations of metrical structure for the GTZAN dataset, each track being annotated multiple times. Inter-annotator agreement and the resulting upper bound on algorithm performance are evaluated. The proposed system reaches 93% of this upper limit and largely outperforms the baseline method.

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Concatenative sound synthesis (CSS) entails synthesising a “target” sound with other sounds collected in a “corpus.” Recent work explores CSS using non-negative matrix factorisation (NMF) to approximate a target sonogram by the product of a corpus sonogram and an activation matrix. In this paper, we propose a number of extensions of NMF-based CSS and present an open MATLAB implementation in a GUI-based application we name NiMFKS. In particular we consider the following extensions: 1) we extend the NMF framework by implementing update rules based on the generalised β-divergence; 2) We add an optional monotonic algorithm for sparse-NMF; 3) we tackle the computational challenges of scaling to big corpora by implementing a corpus pruning preprocessing step; 4) we generalise constraints that may be applied to the activation matrix shape; and 5) we implement new modes of interacting with the procedure by enabling sketching and modifying of the activation matrix. Our application, NiMFKS and source code can be downloaded from here: https: //code.soundsoftware.ac.uk/projects/nimfks.

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