von Neumann T, Boeddeker C, Drude L, et al. Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source Counting, Separation and ASR. In: Proc. Interspeech 2020. ; 2020:3097-3101. doi:10.21437/Interspeech.2020-2519

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

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

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

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

Drude L, Heitkaemper J, Boeddeker C, Haeb-Umbach R. SMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition. ArXiv e-prints. 2019.

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

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

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

Kurz G, Gilitschenski I, Pfaff F, et al. Directional Statistics and Filtering Using libDirectional. In: Journal of Statistical Software 89(4). ; 2019.

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

Heymann J, Khe Chai Sim BL. Improving CTC Using Stimulated Learning for Sequence Modeling. In: ICASSP 2019, Brighton, UK. ; 2019.

Zorila C, Boeddeker C, Doddipatla R, Haeb-Umbach R. An Investigation Into the Effectiveness of Enhancement in ASR Training and Test for Chime-5 Dinner Party Transcription. In: ASRU 2019, Sentosa, Singapore. ; 2019.

Heitkaemper J, Feher T, Freitag M, Haeb-Umbach R. A Study on Online Source Extraction in the Presence of Changing Speaker Positions. In: International Conference on Statistical Language and Speech Processing 2019, Ljubljana, Slovenia. ; 2019.

Martin-Donas JM, Heitkaemper J, Haeb-Umbach R, Gomez AM, Peinado AM. Multi-Channel Block-Online Source Extraction based on Utterance Adaptation. In: INTERSPEECH 2019, Graz, Austria. ; 2019.

Kanda N, Boeddeker C, Heitkaemper J, Fujita Y, Horiguchi S, Haeb-Umbach R. Guided Source Separation Meets a Strong ASR Backend: Hitachi/Paderborn University Joint Investigation for Dinner Party ASR. In: INTERSPEECH 2019, Graz, Austria. ; 2019.

von Neumann T, Kinoshita K, Delcroix M, Araki S, Nakatani T, Haeb-Umbach R. All-neural Online Source Separation, Counting, and Diarization for Meeting Analysis. In: ICASSP 2019, Brighton, UK. ; 2019.

Haeb-Umbach R, Watanabe S, Nakatani T, et al. Speech Processing for Digital Home Assistance: Combining Signal Processing With Deep-Learning Techniques. IEEE Signal Processing Magazine. 2019;36(6):111-124. doi:10.1109/MSP.2019.2918706

Haeb-Umbach R. Lektionen für Alexa &; Co?! DFG forschung 1/2019. Published online 2019:12-15. doi:10.1002/fors.201970104

Gburrek T, Glarner T, Ebbers J, Haeb-Umbach R, Wagner P. Unsupervised Learning of a Disentangled Speech Representation for Voice Conversion. In: Proc. 10th ISCA Speech Synthesis Workshop. ; 2019:81-86. doi:10.21437/SSW.2019-15