no code implementations • LREC 2022 • Sebastian Bayerl, Alexander Wolff von Gudenberg, Florian Hönig, Elmar Noeth, Korbinian Riedhammer
To be able to monitor speech behavior over a long time, the ability to detect stuttering events and modifications in speech could help PWSs and speech pathologists to track the level of fluency.
no code implementations • LREC 2022 • Aniruddha Tammewar, Franziska Braun, Gabriel Roccabruna, Sebastian Bayerl, Korbinian Riedhammer, Giuseppe Riccardi
In this work, we annotate a corpus of spoken personal narratives, with the emotion valence using discrete values.
no code implementations • 24 Oct 2022 • Maximilian Bundscherer, Thomas H. Schmitt, Sebastian Bayerl, Thomas Auerbach, Tobias Bocklet
This paper describes a machine learning approach to determine the abrasive belt wear of wide belt sanders used in industrial processes based on acoustic data, regardless of the sanding process-related parameters, Feed speed, Grit Size, and Type of material.
no code implementations • 16 Jun 2022 • Ilja Baumann, Dominik Wagner, Sebastian Bayerl, Tobias Bocklet
In this work, the task is to determine whether spoken nonwords have been uttered correctly.