M. Sc. Karolin Krüger Room B-Audiolab Kaiserstraße 2, 24143 Kiel, Germany Phone: +49 431 880-6141 E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it. ORCID:  0000-0001-7518-6047 Google scholar: Link

Research: Medical speech analysis and therapy

Speech is an elementary component of communication thus for social interaction, relationships and occupational success. Different medical conditions and neurological diseases like Parkinson´s disease can cause dysphonia. But even high requirements and load in career terms can cause similar symptoms and restrictions of the voice. Patients suffer for example from hoarseness, high effort in speaking and changes in the sound of the voice. Speech therapists can achieve improvements, but they are restricted on subjective measures and their personal auditive perception and experience.

To assist the work of speech therapists and help sufferer, a tool for an objective speech analysis is developed in a first step. It provides different tests to extract basic features from speech in an adjustable and automated examination. Therefore, speech therapists should be able to choose important parameter, different tests and various features to adapt the examination to individual patients. The result is summarized in a medical report to enable a continuous monitoring of the patient’s progress.

In addition, speech therapy could be assisted by providing a training application to enable practicing at home to support the patients progress between therapy sessions. Instananeous feedback while training is important to motivate and support patients as well as to increase success of a therapy. Therefore, training should be adaptable depending on the patient’s needs. Additionally, documentation of the training enables useful insights to the therapist especially for speech in a homelike environment.

Related topics:

• Speech analysis
• Feature extraction
• Pattern recognition

Further interests:

• Real-time digital signal processing
• Signal analysis
• Adaptive filters

Short CV

Publications

1. I. S. Schiller, K. Krüger, T. Lerg, P. Weede, G. Schmidt: Real-Time Voice Quality Alteration: Tackling the Complexity of Simulating Dysphonia, ICVPB 2024, Erlangen, Germany, 2024

2. I. S. Schiller, K. Krüger, P. Weede, M. Sopha, G. Schmidt: Real-Time Modification of Voice Quality using VQ-Synth: Exploring Our Perception of Acoustic Voice Perturbations, Proc. DAGA, Hamburg, Germany, 2024

3. M. J. Finck, K. Krüger, S. Paschen, A. Helmers, G. Schmidt: Analyzing Impaired Speech in Context of Magnetic Resonance-guided Focused Ultrasound Using Convolutional Neural Networks, urn: urn:nbn:de:gbv:8:3-2024-00700-7, Proc. DAGA, Hamburg, Germany, 2024

4. I. S. Schiller, K. Krüger, F. Bin Isamil, S. J. Schlittmeier, G. Schmidt: Voice quality alteration and its potential implications for voice therapy, Journal of the Acoustical Society of America, 154 (4_supplement), A352-A352, 2023

5. J. Hoffmann, C. Bald, T. Schmidt, M. Boueke, E. Engelhardt, K. Krüger, E. Elzenheimer, C. Hansen, W. Maetzler, G. Schmidt: Designing and Validating Magnetic Motion Sensing Approaches with a Real-time Simulation Pipeline, Current Directions in Biomedical Engineering, vol. 9, no. 1, 2023, pp. 455-458, doi: 10.1515/cdbme-2023-1114

6. J. Hoffmann, S. Roldan-Vasco, K. Krüger, F. Niekiel, C. Hansen, W. Maetzler, J. Orozco-Arroyave, G. Schmidt: Pilot Study: Magnetic Motion Analysis for Swallowing Detection Using MEMS Cantilever Actuators, Sensors 2023, 23(7), 3594, doi: 10.3390/s23073594, open access

7. P. Fuchs, K. Krüger, G. Schmidt: Parkinson’s Disease Speech Analysis – Machine-Learning-based Evaluation of Speech Impairments, Proc. DAGA, Hamburg, Germany, 2023

8. J. Winter, K. Krüger, P. Piepjohn, G. Schmidt: Objective Measures for Speech Evaluation, Biosignale Workshop, 2022, Dresden, Germany