University of Bamberg
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Information Systems and Applied Computer Sciences

Chair of Computational Humanities

  1.  University of bamberg
  2. Faculties
  3. Information Systems and Applied Computer Sciences
  4. Subject groups
  5. Applied Computer Science
  6. Chair of Computational Humanities
  7. Publicationen

Publicationen

Publications (since 2022)

[1]
M. Gerhardt, L. Cuccovillo, P. Aichroth, and J. Abeßer, “Audio-Based Tools for Decontextualisation Detection,” in Countering Disinformation in the Era of Generative AI, S. Papadopoulos, K. Bontcheva, V. Mezaris, and R. Rogers, Eds., Cham: Springer Nature Switzerland, 2026, pp. 317–341. doi: 10.1007/978-3-032-11782-3_11.

[2]
J. Abeßer, Z. Liang, and B. Seeber, “Sound Recurrence Analysis for Acoustic Scene Classification,” EURASIP Journal on audio, speech, and music processing, vol. 1, no. 1, pp. 1–15, 2025, doi: 10.1186/s13636-024-00390-2.

[3]
J. Abeßer, H. Lukashevich, S. Ziegler, and J. Bös, “Fortschritte in der automatischen Erkennung von Vogelstimmen,” Akustik Journal, no. 3, pp. 7–16, 2025.

[4]
H. Dilip and J. Abeßer, “A Three-Level Evaluation Protocoll for Acoustic Scene Understanding of Large Language Audio Models,” in Proceedings of the 10th Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE 2025), October 2025, zenodo, 2025, pp. 185–189. doi: 10.5281/zenodo.17251589.

[5]
Y. He, A. M. A. Hosseini, J. Abeßer, L. Jaurigue, A. Raake, and K. Lüdge, “From CNN to Reservoir Computing: A New Perspective on Acoustic Scene Classification,” in 2025 AES International Conference on Artificial Intelligence and Machine Learning for Audio: Queen Mary University of London 8th to 10th, September 2025: Proceedings, 2025, pp. 201–210.

[6]
Y. He, A. Raake, and J. Abeßer, “Enhancing Multiscale Features for Efficient Acoustic Scene Classification with One-Dimensional Separate CNN,” in Proceedings of the 10th Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE 2025), October 2025, Zenodo, 2025, pp. 125–129. doi: 10.5281/zenodo.17251589.

[7]
R. Kumar, S. Grollmisch, and J. Abeßer, “Improvement and Cross-Domain Evaluation of SlowFast Networks,” in 2025 AES International Conference on Artificial Intelligence and Machine Learning for Audio: Queen Mary University of London 8th to 10th, September 2025: Proceedings, 2025, pp. 211–219.

[8]
K. Apostolidis, J. Abeßer, L. Cuccovillo, and V. Mezaris, “Visual and Audio Scene Classification for Detecting Discrepancies in Video: A Baseline Method and Experimental Protocol,” in MAD ’24: Proceedings of the 3rd ACM International Workshop on Multimedia AI against Disinformation, Association for Computing Machinery: New York, NYUnited States, 2024, pp. 30–36. doi: 10.1145/3643491.3660287.

[9]
S. Grollmisch, E. Cano, H. Lukashevich, and J. Abeßer, “Uncertainty in Semi-Supervised Audio Classification: A Novel Extension for FixMatch,” in 31st European Signal Processing Conference (EUSIPCO 2024): proceedings, Piscataway, NJ: IEEE, 2023, pp. 161–165. doi: 10.23919/eusipco58844.2023.10289789.

Previous Publications

A complete list of publications can be found at https://jakobabesser.github.io/