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 

Heymann, J., &; Khe Chai Sim, B. L. (2019). Improving CTC Using Stimulated Learning for Sequence Modeling. In ICASSP 2019, Brighton, UK.

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

Heitkaemper, J., Feher, T., Freitag, M., &; Haeb-Umbach, R. (2019). 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.

Martin-Donas, J. M., Heitkaemper, J., Haeb-Umbach, R., Gomez, A. M., &; Peinado, A. M. (2019). Multi-Channel Block-Online Source Extraction based on Utterance Adaptation. In INTERSPEECH 2019, Graz, Austria.

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

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

Haeb-Umbach, R., Watanabe, S., Nakatani, T., Bacchiani, M., Hoffmeister, B., Seltzer, M. L., Zen, H., &; Souden, M. (2019). Speech Processing for Digital Home Assistance: Combining Signal Processing With Deep-Learning Techniques. IEEE Signal Processing Magazine, 36(6), 111–124.https://doi.org/10.1109/MSP.2019.2918706 

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

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

Ebbers, J., &; Haeb-Umbach, R. (2019). Convolutional Recurrent Neural Network and Data Augmentation for Audio Tagging with Noisy Labels and Minimal Supervision. DCA Workshop, New York, USA.

Ebbers, J., Drude, L., Haeb-Umbach, R., Brendel, A., &; Kellermann, W. (2019). Weakly Supervised Sound Activity Detection and Event Classification in Acoustic Sensor Networks. CAMSAP 2019, Guadeloupe, West Indies.

Nelus, A., Ebbers, J., Haeb-Umbach, R., &; Martin, R. (2019). Privacy-preserving Variational Information Feature Extraction for Domestic Activity Monitoring Versus Speaker Identification. INTERSPEECH 2019, Graz, Austria.

Heymann, J., Bacchiani, M., &; Sainath, T. N. (2018). Performance of Mask Based Statistical Beamforming in a Smart Home Scenario. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 6722–6726).https://doi.org/10.1109/ICASSP.2018.8462372 

Ebbers, J., Nelus, A., Martin, R., &; Haeb-Umbach, R. (2018). Evaluation of Modulation-MFCC Features and DNN Classification for Acoustic Event Detection. In DAGA 2018, München.

Heymann, J., Drude, L., Haeb-Umbach, R., Kinoshita, K., &; Nakatani, T. (2018). Frame-Online DNN-WPE Dereverberation. In IWAENC 2018, Tokio, Japan.

Heitkaemper, J., Heymann, J., &; Haeb-Umbach, R. (2018). Smoothing along Frequency in Online Neural Network Supported Acoustic Beamforming. In ITG 2018, Oldenburg, Germany.

Drude, L., Boeddeker, C., Heymann, J., Kinoshita, K., Delcroix, M., Nakatani, T., &; Haeb-Umbach, R. (2018). Integration neural network based beamforming and weighted prediction error dereverberation. In INTERSPEECH 2018, Hyderabad, India.

Drude, L., Heymann, J., Boeddeker, C., &; Haeb-Umbach, R. (2018). NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing. In ITG 2018, Oldenburg, Germany.

Despotovic, V., Walter, O., &; Haeb-Umbach, R. (2018). Machine learning techniques for semantic analysis of dysarthric speech: An experimental study. Speech Communication 99 (2018) 242-251 (Elsevier B.V.).