L. Drude and R. Haeb-Umbach, “Integration of Neural Networks and Probabilistic Spatial Models for Acoustic Blind Source Separation,” IEEE Journal of Selected Topics in Signal Processing, 2019.
LibreCat: /record/12890
DOI: 10.1109/JSTSP.2019.2912565

J. Heymann and B. L. Khe Chai Sim, “Improving CTC Using Stimulated Learning for Sequence Modeling,” in ICASSP 2019, Brighton, UK, 2019.
LibreCat: /record/15812

C. Zorila, C. Boeddeker, R. Doddipatla, and R. Haeb-Umbach, “An Investigation Into the Effectiveness of Enhancement in ASR Training and Test for Chime-5 Dinner Party Transcription,” in ASRU 2019, Sentosa, Singapore, 2019.
LibreCat: /record/15816

J. Heitkaemper, T. Feher, M. Freitag, and R. Haeb-Umbach, “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.
LibreCat: /record/14822

J. M. Martin-Donas, J. Heitkaemper, R. Haeb-Umbach, A. M. Gomez, and A. M. Peinado, “Multi-Channel Block-Online Source Extraction based on Utterance Adaptation,” in INTERSPEECH 2019, Graz, Austria, 2019.
LibreCat: /record/14824

N. Kanda, C. Boeddeker, J. Heitkaemper, Y. Fujita, S. Horiguchi, and R. Haeb-Umbach, “Guided Source Separation Meets a Strong ASR Backend: Hitachi/Paderborn University Joint Investigation for Dinner Party ASR,” in INTERSPEECH 2019, Graz, Austria, 2019.
LibreCat: /record/14826

T. von Neumann, K. Kinoshita, M. Delcroix, S. Araki, T. Nakatani, and R. Haeb-Umbach, “All-neural Online Source Separation, Counting, and Diarization for Meeting Analysis,” in ICASSP 2019, Brighton, UK, 2019.
LibreCat: /record/13271

R. Haeb-Umbach et al., “Speech Processing for Digital Home Assistance: Combining Signal Processing With Deep-Learning Techniques,”10.1109/MSP.2019.2918706__IEEE Signal Processing Magazine, vol. 36, no. 6, pp. 111–124, 2019, doi:10.1109/MSP.2019.2918706 .
LibreCat: /record/15814
DOI: 10.1109/MSP.2019.2918706

R. Haeb-Umbach, “Lektionen für Alexa &; Co?!,”10.1002/fors.201970104__DFG forschung 1/2019, pp. 12–15, 2019, doi:10.1002/fors.201970104 .
LibreCat: /record/19450
DOI: 10.1002/fors.201970104

T. Gburrek, T. Glarner, J. Ebbers, R. Haeb-Umbach, and P. Wagner, “Unsupervised Learning of a Disentangled Speech Representation for Voice Conversion,”10.21437/SSW.2019-15__in Proc. 10th ISCA Speech Synthesis Workshop, Vienna, 2019, pp. 81–86, doi:10.21437/SSW.2019-15 .
LibreCat: /record/15237
DOI: 10.21437/SSW.2019-15

J. Ebbers and R. Haeb-Umbach, “Convolutional Recurrent Neural Network and Data Augmentation for Audio Tagging with Noisy Labels and Minimal Supervision,” 2019.
LibreCat: /record/15794

J. Ebbers, L. Drude, R. Haeb-Umbach, A. Brendel, and W. Kellermann, “Weakly Supervised Sound Activity Detection and Event Classification in Acoustic Sensor Networks,” 2019.
LibreCat: /record/15796

A. Nelus, J. Ebbers, R. Haeb-Umbach, and R. Martin, “Privacy-preserving Variational Information Feature Extraction for Domestic Activity Monitoring Versus Speaker Identification,” 2019.
LibreCat: /record/15792

J. Heymann, M. Bacchiani, and T. N. Sainath, “Performance of Mask Based Statistical Beamforming in a Smart Home Scenario,” in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018, pp. 6722–6726.
LibreCat: /record/18107
DOI: 10.1109/ICASSP.2018.8462372

J. Ebbers, A. Nelus, R. Martin, and R. Haeb-Umbach, “Evaluation of Modulation-MFCC Features and DNN Classification for Acoustic Event Detection,” in DAGA 2018, München, 2018.
LibreCat: /record/11760

J. Heymann, L. Drude, R. Haeb-Umbach, K. Kinoshita, and T. Nakatani, “Frame-Online DNN-WPE Dereverberation,” in IWAENC 2018, Tokio, Japan, 2018.
LibreCat: /record/11835

J. Heitkaemper, J. Heymann, and R. Haeb-Umbach, “Smoothing along Frequency in Online Neural Network Supported Acoustic Beamforming,” in ITG 2018, Oldenburg, Germany, 2018.
LibreCat: /record/11837

L. Drude et al., “Integration neural network based beamforming and weighted prediction error dereverberation,” in INTERSPEECH 2018, Hyderabad, India, 2018.
LibreCat: /record/11872

L. Drude, J. Heymann, C. Boeddeker, and R. Haeb-Umbach, “NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing,” in ITG 2018, Oldenburg, Germany, 2018.
LibreCat: /record/11873

V. Despotovic, O. Walter, and R. Haeb-Umbach, “Machine learning techniques for semantic analysis of dysarthric speech: An experimental study,” Speech Communication 99 (2018) 242-251 (Elsevier B.V.), 2018.
LibreCat: /record/11916