Sync Toolbox (JOSS)



Sync Toolbox is a Python package, which comprises all components of a music synchronization pipeline that is robust, efficient, and accurate.

The toolbox’s core technology is based on dynamic time warping (DTW). Using suitable feature representations and cost measures, DTW brings the feature sequences into temporal correspondence.

To account for efficiency, robustness, and accuracy, Sync Toolbox uses a combination of multiscale DTW (MsDTW), memory-restricted MsDTW (MrMsDTW), and high-resolution music synchronization.

NMF Toolbox (DAFx 2019)



Nonnegative matrix factorization (NMF) is a family of methods widely used for information retrieval across domains including text, images, and audio. Within music processing, NMF has been used for tasks such as transcription, source separation, and structure analysis. Prior work has shown that initialization and constrained update rules can drastically improve the chances of NMF converging to a musically meaningful solution. Along these lines we present the NMF toolbox, containing MATLAB and Python implementations of conceptually distinct NMF variants—in particular, this paper gives an overview for two algorithms. The first variant, called nonnegative matrix factor deconvolution (NMFD), extends the original NMF algorithm to the convolutive case, enforcing the temporal order of spectral templates. The second variant, called diagonal NMF, supports the development of sparse diagonal structures in the activation matrix. Our toolbox contains several demo applications and code examples to illustrate its potential and functionality. By providing MATLAB and Python code on a documentation website under a GNU-GPL license, as well as including illustrative examples, our aim is to foster research and education in the field of music processing.