Jörg Bitzer
Fraunhofer Society
8 Papers
35 Citations
Jörg Bitzer is an academic researcher from Fraunhofer Society. The author has contributed to research in topics: Noise & Health care. The author has an hindex of 4, co-authored 8 publications. Previous affiliations of Jörg Bitzer include Jade University of Applied Sciences.
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Papers
The Lower Saxony research network design of environments for ageing: towards interdisciplinary research on information and communication technologies in ageing societies
Reinhold Haux,Andreas Hein,Marco Eichelberg,Jens-E. Appell,Hans-Jürgen Appelrath,Christian Bartsch,Thomas Bisitz,Jörg Bitzer,Matthias Blau,Susanne Boll,Michael Buschermöhle,Felix Busching,Birte Erdmann,Uwe Fachinger,Juliane Felber,Tobias Fleuren,Matthias Gietzelt,Stefan Goetze,Mehmet Gövercin,Axel Helmer,Wilko Heuten,Volker Hohmann,Rainer Huber,Manfred Hülsken-Giesler,Gerold Jacobs,Riana Kayser,Arno Kerling,Timo Klingeberg,Yvonne Költzsch,Harald Künemund,Jennifer Kunze,Wolfram Ludwig,Michael Marschollek,Birger Martens,Markus Meis,Eike Michael Meyer,Jochen Meyer,Wolfgang Nebel,Franz J. Neyer,Petra-Karin Okken,Hartmut Remmers,Lars Rölker-Denker,Thomas Rohdenburg,Meinhard Schilling,Gisela C. Schulze,Bianying Song,Jens Spehr,Elisabeth Steinhagen-Thiessen,Uwe Tegtbur,Wilfried Thoben,Peter W. J. van Hengel,Stefan Wabnik,Friedrich M. Wahl,S. Wegel,Olaf Wilken,Simon Winkelbach,Thorben Wist,Manfred Wittrock,Klaus-Hendrik Wolf,Lars Wolf,Melanie Zokoll-Van Derlaan +60 more
TL;DR: This publication informs about the goals and structure of GAL, including first outcomes, as well as to discuss the potentials and possible barriers of such highly interdisciplinary research projects in the field of health-enabling technologies for pervasive healthcare.
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Robust Drone Detection for Acoustic Monitoring Applications
Mattes Ohlenbusch,Aike Ahrens,Christian Rollwage,Jörg Bitzer +3 more
- 24 Jan 2021
TL;DR: In this article, the typical feature set is extended to increase separation of background noise and the UAV signature noise, and the decision algorithm utilized is support vector machine (SVM) classification.
9
Adaptive Compressive Onset-Enhancement for Improved Speech Intelligibility in Noise and Reverberation.
Felicitas Bederna,Henning Schepker,Christian Rollwage,Simon Doclo,Arne Pusch,Jörg Bitzer,Jan Rennies +6 more
- 25 Oct 2020
TL;DR: This paper uses instrumental measures as well as subjective ratings of listening effort for acoustic scenarios with different reverberation times and realistic signal-to-noise ratios to evaluate a new combination of a noise-dependent and a reverberationdependent algorithm implemented in a common framework.
9
Individual hearing aid benefit: Ecological momentary assessment of hearing abilities
Petra von Gablenz,Ulrik Kowalk,Jörg Bitzer,Markus Meis,Inga Holube +4 more
- 01 Jan 2019
TL;DR: An EMA study to examine how HA uptake changes the perception of everyday hearing abilities and a considerable individual variability regarding the type of reported events, the distribution and position of assessments is shown.
Joint estimation of pitch and direction of arrival: improving robustness and accuracy for multi-speaker scenarios
TL;DR: Several extensions to a recently presented joint direction of arrival (DOA) and pitch estimation method are proposed, increasing its robustness in multi-speaker scenarios, noise, and reverberation, and improving tracking for moving and even intersecting speakers.