• [1] S. P. Bayerl, F. Hönig, J. Reister, and K. Riedhammer, “Towards Automated Assessment of Stuttering and Stuttering Therapy,” in International Conference on Text, Speech, and Dialogue, 2020 [Online]. Available at: https://arxiv.org/abs/2006.09222
  • [2] S. P. Bayerl et al., “Offline Model Guard: Secure and Private ML on Mobile Devices,” in 23. Design, Automation and Test in Europe Conference (DATE ’20), 2020.


  • [1] S. P. Bayerl and K. Riedhammer, “A Comparison of Hybrid and End-to-End Models for Syllable Recognition,” in International Conference on Text, Speech, and Dialogue, 2019, pp. 352–360 [Online]. Available at: https://arxiv.org/abs/1909.12232
  • [2] M. Wenninger, S. P. Bayerl, J. Schmidt, and K. Riedhammer, “Timage–A Robust Time Series Classification Pipeline,” in International Conference on Artificial Neural Networks, 2019, pp. 450–461 [Online]. Available at: https://arxiv.org/abs/1909.09149
  • [3] J. C. Vásquez-Correa et al., “Apkinson: A Mobile Solution for Multimodal Assessment of Patients with Parkinson’s Disease,” Proc. Interspeech 2019, pp. 964–965, 2019.
  • [4] S. P. Bayerl et al., “Privacy-preserving speech processing via STPC and TEEs (Poster),” 2019.