von Neumann, T., Boeddeker, C., Kinoshita, K., Delcroix, M., &; Haeb-Umbach, R. (2021). Speeding Up Permutation Invariant Training for Source Separation. Speech Communication; 14th ITG Conference. Speech Communication; 14th ITG Conference, Kiel.

Ebbers, J., &; Haeb-Umbach, R. (2021). Self-Trained Audio Tagging and Sound Event Detection in Domestic Environments. Proceedings of the 6th Detection and Classification of Acoustic Scenes and Events 2021 Workshop (DCA), 226–230.

Ebbers, J., Keyser, M. C., &; Haeb-Umbach, R. (2021). Adapting Sound Recognition to A New Environment Via Self-Training. Proceedings of the 29th European Signal Processing Conference (EUSIPCO), 1135–1139.

Rohlfing, K. J., Cimiano, P., Scharlau, I., Matzner, T., Buhl, H. M., Buschmeier, H., Esposito, E., Grimminger, A., Hammer, B., Haeb-Umbach, R., Horwath, I., Hüllermeier, E., Kern, F., Kopp, S., Thommes, K., Ngonga Ngomo, A.-C., Schulte, C., Wachsmuth, H., Wagner, P., &; Wrede, B. (2021). Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems. IEEE Transactions on Cognitive and Developmental Systems, 13(3), 717–728.https://doi.org/10.1109/tcds.2020.3044366 

Haeb-Umbach, R. (2020). Sprachtechnologien für Digitale Assistenten. In R. Böck, I. Siegert, &; A. Wendemuth (Eds.), Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2020 (pp. 227–234). TUDpress, Dresden.

Boeddeker, C., Cord-Landwehr, T., Heitkaemper, J., Zorila, C., Hayakawa, D., Li, M.,  Haeb-Umbach, R. (2020). Towards a speaker diarization system for the CHiME 2020 dinner party transcription. In Proc. CHiME 2020 Workshop on Speech Processing in Everyday Environments.

Nakatani, T., Boeddeker, C., Kinoshita, K., Ikeshita, R., Delcroix, M., &; Haeb-Umbach, R. (2020). Jointly optimal denoising, dereverberation, and source separation. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 1–1.https://doi.org/10.1109/TASLP.2020.3013118 

Heitkaemper, J., Jakobeit, D., Boeddeker, C., Drude, L., &; Haeb-Umbach, R. (2020). Demystifying TasNet: A Dissecting Approach. ICASSP 2020 Virtual Barcelona Spain.

Heitkaemper, J., Schmalenstroeer, J., &; Haeb-Umbach, R. (2020). Statistical and Neural Network Based Speech Activity Detection in Non-Stationary Acoustic Environments. INTERSPEECH 2020 Virtual Shanghai China.

von Neumann, T., Kinoshita, K., Drude, L., Boeddeker, C., Delcroix, M., Nakatani, T., &; Haeb-Umbach, R. (2020). End-to-End Training of Time Domain Audio Separation and Recognition. ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 7004–7008.https://doi.org/10.1109/ICASSP40776.2020.9053461 

von Neumann, T., Boeddeker, C., Drude, L., Kinoshita, K., Delcroix, M., Nakatani, T., &; Haeb-Umbach, R. (2020). Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source Counting, Separation and ASR. Proc. Interspeech 2020, 3097–3101.https://doi.org/10.21437/Interspeech.2020-2519 

Gburrek, T., Schmalenstroeer, J., Brendel, A., Kellermann, W., &; Haeb-Umbach, R. (2020). Deep Neural Network based Distance Estimation for Geometry Calibration in Acoustic Sensor Network. European Signal Processing Conference (EUSIPCO).

Kinoshita, K., von Neumann, T., Delcroix, M., Nakatani, T., &; Haeb-Umbach, R. (2020). Multi-Path RNN for Hierarchical Modeling of Long Sequential Data and its Application to Speaker Stream Separation. Proc. Interspeech 2020, 2652–2656.https://doi.org/10.21437/Interspeech.2020-2388 

Ebbers, J., &; Haeb-Umbach, R. (2020). Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-Supervised Sound Event Detection. Proceedings of the Detection and Classification of Acoustic Scenes and Events 2020 Workshop (DCA).

Haeb-Umbach, R. (2019). Lektionen für Alexa \'26; Co?! Forschung, 44(1), 12–15.https://doi.org/10.1002/fors.201970104 

Drude, L., Heitkaemper, J., Boeddeker, C., &; Haeb-Umbach, R. (2019). SMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition. ArXiv E-Prints.

Drude, L., Heymann, J., &; Haeb-Umbach, R. (2019). Unsupervised training of neural mask-based beamforming. In INTERSPEECH 2019, Graz, Austria.

Drude, L., Hasenklever, D., &; Haeb-Umbach, R. (2019). Unsupervised Training of a Deep Clustering Model for Multichannel Blind Source Separation. In ICASSP 2019, Brighton, UK.

Heymann, J., Drude, L., Haeb-Umbach, R., Kinoshita, K., &; Nakatani, T. (2019). Joint Optimization of Neural Network-based WPE Dereverberation and Acoustic Model for Robust Online ASR. In ICASSP 2019, Brighton, UK.

Kurz, G., Gilitschenski, I., Pfaff, F., Drude, L., Hanebeck, U. D., Haeb-Umbach, R., &; Siegwart, R. Y. (2019). Directional Statistics and Filtering Using libDirectional. In Journal of Statistical Software 89(4).