Finn Röhrdanz

		M. Sc. Finn Röhrdanz Room F-006 Kaiserstraße 2, 24143 Kiel, Germany Phone: +49 431 880-6144 E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it. ORCID: 0009-0002-6502-5965

Research: Underwater signal transmission

The transmission and reception of signals in the underwater environment impose some challenges due to the behavior of the underwater channel. For the transmission of signals over large ranges, the underwater channel is only suitable for acoustic signal transmission. The attenuation, multipath signal pathway as well as slow speed of sound in water imposes some major challenges. The aim of the research is to overcome the challenges by means of signal processing techniques. The transmitted signal is affected by noise and artifacts due to the multipath environment. Restoring the transmitted signals is essential to be able to perform communication between underwater nodes. Typical examples are the communication with divers and submarines. Both traditional signal processing and newer approaches such as neural networks are part of the research.

Further interests:

SONAR
3D modeling and design
Neural networks

Short CV

Time span	Details
2023 - current	Research Assistant at the Christian-Albrechts-Universität zu Kiel, Kiel, Germany
2021 - 2023	M.Sc. in Electrical Engineering and Information Theory Christian-Albrechts-Universität zu Kiel, Germany
2020 - 2021	Moeller Operating Engineering (Expert for the certification of combined heat and powerplants)
2015 - 2021	B.Sc. in Electrical Engineering and Information Theory Christian-Albrechts-Universität zu Kiel, Germany

Publications

F. Kühne, B. Kaulen, C. Kanarski, F. Röhrdanz, K. Gussow, G. Schmidt: Detektion und Klassifikation von Objekten aus von SONAR-Systemen erstellten Plots mithilfe von künstlicher Intelligenz, Proc. DAGA, Germany, 2024
K. Gussow, B. Kaulen, F. Kühne, C. Kanarski, F. Röhrdanz, M. Driesen, S. Rautenberg, J. Abshagen, E. Mackensen, D. Meyners, E. Quandt, G. Schmidt: Untersuchung des Einflusses verschiedener Array- Öffnungswinkel bei MIMO-SONAR-Systemen, Proc. DAGA, Germany, 2024

We are delighted to announce that Marten Finck has been awarded the GaS prize for his Master's thesis on "Evaluation of Speech Quality Using Machine Learning".

In his work, he investigated possible side effects of magnetic resonance-guided focussed ultrasound treatment (MRgFUS) on speech quality in patients with neurological diseases such as Parkinson's disease and essential tremor. This innovative and non-invasive treatment method is used to reduce tremor, i.e. the shaking of limbs.

To evaluate the effects on speech, pre- and post-operative speech recordings of 56 patients were analysed: Speech quality was assessed in five categories (monotony, clarity, fluency, auditory effort and vocal tremor) through a survey with 21 participants and used to create a convolutional neural network (CNN). This generates an objective assessment of speech quality using mel frequency cepstral coefficients (MFCCs), fundamental frequency and loudness. A mean absolute error (MAE) of 0.81 on a scale of 0 to 10 was achieved, compared to a standard deviation of 0.67 for the survey participants compared to a reference assessment. The evaluation of the survey revealed minor positive and negative changes in speech quality, which were balanced overall and tended to indicate natural speech variations in connection with the patients' underlying illnesses.

Congratulations on this well-deserved honour!

M. Sc. Finn Röhrdanz

Research: Underwater signal transmission

Further interests:

Short CV

Publications

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