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Large music content libraries often comprise multiple versions of a piece ofmusic. To establish a link between different versions, automatic musicalignment methods map each position in one version to a corresponding positionin another version. Due to the leeway in interpreting a piece, any two versionscan differ significantly, for example, in terms of local tempo, articulation,or playing style. For a given pair of versions, these differences can besignificant such that even state-of-the-art methods fail to identify a correctalignment. In this paper, we present a novel method that increases therobustness for difficult to align cases. Instead of aligning only pairs ofversions as done in previous methods, our method aligns multiple versions in ajoint manner. This way, the alignment can be computed by comparing each versionnot only with one but with several versions, which stabilizes the comparisonand leads to an increase in alignment robustness. Using recordings from theMazurka Project, the alignment error for our proposed method was 14% lower onaverage compared to a state-of-the-art method, with significantly less outliers(standard deviation 53% lower).

Robust Joint Alignment of Multiple Versions of a Piece of Music