Matthias Echternach
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Matthias Echternach is a Professor at Ludwig Maximilian University of Munich, Germany. His research focuses on vocal stability, voice parameters, and the application of machine learning in assessing hoarseness severity. He has published several articles examining the effects of hydration on voice, the dynamics of wind instruments, and techniques in vocal health and onset. His work integrates advanced methodologies, including high-speed videoendoscopy and acoustic signal analysis.
Recent Grants
Grant: Close
Aerosol dispersion
Open Date: 2020-08-01
Close Date: 2022-10-01
Grant: Close
High Speed Digital Imaging
Open Date: 2017-09-01
Close Date: 2020-08-01
Grant: Close
High Speed Digital Imaging
Open Date: 2013-05-01
Close Date: 2016-12-01
Grant: Close
Dynamic Real Time MRI
Open Date:
Close Date:
Articles (20)
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Research Article on Advanced Machine Learning Applications
Year:
2024
Collaborators (3)
John Doe
Professor of Computer Science
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John Doe
Professor of Computer Science
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John Doe
Professor of Computer Science
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