64 citations · 91 across the 9 of their papers we have counts for
5 papers · 1 filter
Local Periodicity-Based Beat Tracking for Expressive Classical Piano Music
Ching-Yu Chiu, Meinard Müller, Matthew E. P. Davies +2
To model the periodicity of beats, state-of-the-art beat tracking systems use "post-processing trackers" (PPTs) that rely on several empirically determined global assumptions for t…
Stabilizing Training with Soft Dynamic Time Warping: A Case Study for Pitch Class Estimation with Weakly Aligned Targets
Johannes Zeitler, Simon Deniffel, Michael Krause +1
Soft dynamic time warping (SDTW) is a differentiable loss function that allows for training neural networks from weakly aligned data. Typically, SDTW is used to iteratively compute…
An Analysis Method for Metric-Level Switching in Beat Tracking
Ching-Yu Chiu, Meinard Müller, Matthew E. P. Davies +2
For expressive music, the tempo may change over time, posing challenges to tracking the beats by an automatic model. The model may first tap to the correct tempo, but then may fail…
Towards Audio Domain Adaptation for Acoustic Scene Classification using Disentanglement Learning
Jakob Abeßer, Meinard Müller
The deployment of machine listening algorithms in real-life applications is often impeded by a domain shift caused for instance by different microphone characteristics. In this pap…
Unsupervised Domain Adaptation for Acoustic Scene Classification Using Band-Wise Statistics Matching
Alessandro Ilic Mezza, Emanuël A. P. Habets, Meinard Müller +1
The performance of machine learning algorithms is known to be negatively affected by possible mismatches between training (source) and test (target) data distributions. In fact, th…