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eess.AS2023
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…
eess.AS2021
Manifold learning-supported estimation of relative transfer functions for spatial filtering
Andreas Brendel, Johannes Zeitler, Walter Kellermann
Many spatial filtering algorithms used for voice capture in, e.g., teleconferencing applications, can benefit from or even rely on knowledge of Relative Transfer Functions (RTFs).…