research
- Voice analysis for Healthcare and Wellbeing applications
- Effects of Neurological, Neurodegenerative and Psychological diseases on voice
- Using voice to unobtrusively monitor health status in everyday life
publications
1. González-Machorro, M., Reichel, U., Hecker, P., Hammer, H., Sagha, H., Eyben, F., Hoepner, R., & Schuller, B. W. (2025). Speech-based depressive mood detection in the presence of multiple sclerosis: A cross-corpus and cross-lingual study. *arXiv preprint* arXiv:2508.18092.
2. Hecker, P., González-Machorro, M., Sagha, H., Dudeja, S., Kahlau, M., Eyben, F., Schuller, B., & Arnrich, B. (2025). Mental wellbeing at sea: A prototype to collect speech data in maritime settings. In *Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies — Volume 2: HEALTHINF* (pp. 29–40). SciTePress. https://doi.org/10.5220/0013093700003911
3. Kappattanavar, A. M., Hecker, P., Moontaha, S., Steckhan, N., & Arnrich, B. (2023). Food choices after cognitive load: An affective computing approach. *Sensors, 23*(14).
4. González-Machorro, M.*, Hecker, P.*, Reichel, U. D., Hammer, H. N., Hoepner, R., Pedrotti, L., Zmutt, A., Sagha, H., van Beek, J., Eyben, F., Schuller, D. M., Schuller, B. W., & Arnrich, B. (2023). Towards supporting an early diagnosis of multiple sclerosis using vocal features. In *Interspeech 2023* (pp. 1518–1522).
5. Moontaha, S., Kappattanavar, A. M., Hecker, P., & Arnrich, B. (2023). Wearable EEG-based cognitive load classification by personalized and generalized model using brain asymmetry. *Unpublished manuscript.*
6. Hecker, P., Kappattanavar, A. M., Schmitt, M., Moontaha, S., Wagner, J., Eyben, F., Schuller, B. W., & Arnrich, B. (2022). Quantifying cognitive load from voice using transformer-based models and a cross-dataset evaluation. In *2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)* (pp. 337–344).
7. Hecker, P., Steckhan, N., Eyben, F., Schuller, B. W., & Arnrich, B. (2022). Voice analysis for neurological disorder recognition: A systematic review and perspective on emerging trends. *Frontiers in Digital Health, 4.*
8. Hecker, P., Pokorny, F. B., Bartl-Pokorny, K. D., Reichel, U., Ren, Z., Hantke, S., Eyben, F., Schuller, D. M., Arnrich, B., & Schuller, B. W. (2021). Speaking Corona? Human and machine recognition of COVID-19 from voice. In *Proceedings of Interspeech 2021* (pp. 1029–1033).
9. Hernández, N., García-Constantino, M., Beltrán, J., Hecker, P., Favela, J., Cleland, I., López, H., Arnrich, B., & McChesney, I. (2020). Prototypical system to detect anxiety manifestations by acoustic patterns in patients with dementia. *EAI Endorsed Transactions on Pervasive Health and Technology, 5*(19).
personal
- Since 2019: AI Researcher in Digital Healthcare and Wellbeing at audEERING GmbH
- Joint PhD with the Connected Healthcare group and audEERING GmbH
- 2018 - 2019: Research Internship at audEERING GmbH
- 2018: Research Assistant at Applied Rehabilitation Technology Lab, Universitätsmedizin Göttingen
- 2014 - 2018: Master of Science (M.Sc.), Developmental, Neural and Behavioural Biology with focus on Computational Neuroscience at Georg-August-Universität Göttingen
- 2010 - 2014: Bachelor of Science (B.Sc.), Biology at Freie Universität Berlin