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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).

Drude, L., &; Haeb-Umbach, R. (2019). Integration of Neural Networks and Probabilistic Spatial Models for Acoustic Blind Source Separation. IEEE Journal of Selected Topics in Signal Processing.https://doi.org/10.1109/JSTSP.2019.2912565