H. Afifi, H. Karl, T. Gburrek, and J. Schmalenstroeer, “Data-driven Time Synchronization in Wireless Multimedia Networks,”10.1109/iwcmc55113.2022.9824980__2022, doi:10.1109/iwcmc55113.2022.9824980 .
LibreCat: /record/33806
DOI: 10.1109/iwcmc55113.2022.9824980

K. Kinoshita, T. von Neumann, M. Delcroix, C. Boeddeker, and R. Haeb-Umbach, “Utterance-by-utterance overlap-aware neural diarization with Graph-PIT,”10.21437/Interspeech.2022-11408__in Proc. Interspeech 2022, 2022, pp. 1486–1490, doi:10.21437/Interspeech.2022-11408 .
LibreCat: /record/33958
DOI: 10.21437/Interspeech.2022-11408

T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, and R. Haeb-Umbach, “SA-SDR: A Novel Loss Function for Separation of Meeting Style Data,”10.1109/icassp43922.2022.9746757__2022, doi:10.1109/icassp43922.2022.9746757 .
LibreCat: /record/33819
DOI: 10.1109/icassp43922.2022.9746757

T. Cord-Landwehr, T. von Neumann, C. Boeddeker, and R. Haeb-Umbach, “MMS-MSG: A Multi-purpose Multi-Speaker Mixture Signal Generator,” presented at the 2022 International Workshop on Acoustic Signal Enhancement (IWAENC), Bamberg, 2022.
LibreCat: /record/33847
arXiv: 2209.11494

T. Cord-Landwehr, C. Boeddeker, T. von Neumann, C. Zorila, R. Doddipatla, and R. Haeb-Umbach, “Monaural source separation: From anechoic to reverberant environments,” presented at the 2022 International Workshop on Acoustic Signal Enhancement (IWAENC), 2022.
LibreCat: /record/33848
arXiv: 2111.07578

T. Gburrek, J. Schmalenstroeer, and R. Haeb-Umbach, “On Synchronization of Wireless Acoustic Sensor Networks in the Presence of Time-Varying Sampling Rate Offsets and Speaker Changes,”10.1109/icassp43922.2022.9746284__2022, doi:10.1109/icassp43922.2022.9746284 .
LibreCat: /record/33807
DOI: 10.1109/icassp43922.2022.9746284

C. Grimm, T. Fei, E. Warsitz, R. Farhoud, T. Breddermann, and R. Haeb-Umbach, “Warping of Radar Data Into Camera Image for Cross-Modal Supervision in Automotive Applications,”10.1109/TVT.2022.3182411__IEEE Transactions on Vehicular Technology, vol. 71, no. 9, pp. 9435–9449, 2022, doi:10.1109/TVT.2022.3182411 .
LibreCat: /record/33451
DOI: 10.1109/TVT.2022.3182411

J. Ebbers and R. Haeb-Umbach, Pre-Training And Self-Training For Sound Event Detection In Domestic Environments. 2022.
LibreCat: /record/49113

J. Wiechmann, T. Glarner, F. Rautenberg, P. Wagner, and R. Haeb-Umbach, “Technically enabled explaining of voice characteristics,” Bielefeld, 2022.
LibreCat: /record/33696

M. Kuhlmann, F. Seebauer, J. Ebbers, P. Wagner, and R. Haeb-Umbach, “Investigation into Target Speaking Rate Adaptation for Voice Conversion,”10.21437/interspeech.2022-10740__2022, doi:10.21437/interspeech.2022-10740 .
LibreCat: /record/33857
DOI: 10.21437/interspeech.2022-10740

T. Gburrek, J. Schmalenstroeer, J. Heitkaemper, and R. Haeb-Umbach, “Informed vs. Blind Beamforming in Ad-Hoc Acoustic Sensor Networks for Meeting Transcription,”10.1109/IWAENC53105.2022.9914772__presented at the 17th International Workshop on Acoustic Signal Enhancement (IWAENC 2022),10.1109/IWAENC53105.2022.9914772__Bamberg, Germany , 2022, doi:10.1109/IWAENC53105.2022.9914772 .
LibreCat: /record/33808
DOI: 10.1109/IWAENC53105.2022.9914772

T. Gburrek, C. Boeddeker, T. von Neumann, T. Cord-Landwehr, J. Schmalenstroeer, and R. Haeb-Umbach, A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network. arXiv, 2022.
LibreCat: /record/33816
DOI: 10.48550/ARXIV.2205.00944

J. Ebbers, R. Haeb-Umbach, and R. Serizel, “Threshold Independent Evaluation of Sound Event Detection Scores,” 2022.
LibreCat: /record/34072

R. Haeb-Umbach, J. Heymann, L. Drude, S. Watanabe, M. Delcroix, and T. Nakatani, “Far-Field Automatic Speech Recognition,” Proceedings of the IEEE, vol. 109, no. 2, pp. 124–148, 2021.
LibreCat: /record/21065
DOI: 10.1109/JPROC.2020.3018668

W. Zhang et al., “End-to-End Dereverberation, Beamforming, and Speech Recognition with Improved Numerical Stability and Advanced Frontend,”10.1109/icassp39728.2021.9414464__2021, doi:10.1109/icassp39728.2021.9414464 .
LibreCat: /record/28256
DOI: 10.1109/icassp39728.2021.9414464

C. Li et al., “ESPnet-SE: End-To-End Speech Enhancement and Separation Toolkit Designed for ASR Integration,”10.1109/slt48900.2021.9383615__2021, doi:10.1109/slt48900.2021.9383615 .
LibreCat: /record/28262
DOI: 10.1109/slt48900.2021.9383615

C. Li et al., “Dual-Path RNN for Long Recording Speech Separation,”10.1109/slt48900.2021.9383514__2021, doi:10.1109/slt48900.2021.9383514 .
LibreCat: /record/28261
DOI: 10.1109/slt48900.2021.9383514

J. Heitkaemper, J. Schmalenstroeer, V. Ion, and R. Haeb-Umbach, “A Database for Research on Detection and Enhancement of Speech Transmitted over HF links,” in Speech Communication; 14th ITG-Symposium, 2021, pp. 1–5.
LibreCat: /record/24000

C. Boeddeker, F. Rautenberg, and R. Haeb-Umbach, “A Comparison and Combination of Unsupervised Blind Source Separation  Techniques,” presented at the ITG Conference on Speech Communication, Kiel, 2021.
LibreCat: /record/44843
arXiv: 2106.05627

C. Boeddeker et al., “Convolutive Transfer Function Invariant SDR Training Criteria for Multi-Channel Reverberant Speech Separation,”10.1109/icassp39728.2021.9414661__2021, doi:10.1109/icassp39728.2021.9414661 .
LibreCat: /record/28259
DOI: 10.1109/icassp39728.2021.9414661

J. Schmalenstroeer, J. Heitkaemper, J. Ullmann, and R. Haeb-Umbach, “Open Range Pitch Tracking for Carrier Frequency Difference Estimation from HF Transmitted Speech,” in 29th European Signal Processing Conference (EUSIPCO), 2021, pp. 1–5.
LibreCat: /record/23998

T. Gburrek, J. Schmalenstroeer, and R. Haeb-Umbach, “Geometry calibration in wireless acoustic sensor networks utilizing DoA and distance information,”10.1186/s13636-021-00210-x__EURASIP Journal on Audio, Speech, and Music Processing, 2021, doi:10.1186/s13636-021-00210-x .
LibreCat: /record/22528
DOI: 10.1186/s13636-021-00210-x

T. Gburrek, J. Schmalenstroeer, and R. Haeb-Umbach, “Iterative Geometry Calibration from Distance Estimates for Wireless Acoustic Sensor Networks,”10.1109/icassp39728.2021.9413831__2021, doi:10.1109/icassp39728.2021.9413831 .
LibreCat: /record/23994
DOI: 10.1109/icassp39728.2021.9413831

T. Gburrek, J. Schmalenstroeer, and R. Haeb-Umbach, “On Source-Microphone Distance Estimation Using Convolutional Recurrent Neural Networks,” in Speech Communication; 14th ITG-Symposium, 2021, pp. 1–5.
LibreCat: /record/23999

A. Chinaev, G. Enzner, T. Gburrek, and J. Schmalenstroeer, “Online Estimation of Sampling Rate Offsets in Wireless Acoustic Sensor Networks with Packet Loss,” in 29th European Signal Processing Conference (EUSIPCO), 2021, pp. 1–5.
LibreCat: /record/23997

J. Ebbers, M. Kuhlmann, T. Cord-Landwehr, and R. Haeb-Umbach, “Contrastive Predictive Coding Supported Factorized Variational Autoencoder for Unsupervised Learning of Disentangled Speech Representations,” in Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, pp. 3860–3864.
LibreCat: /record/29304

T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, and R. Haeb-Umbach, “Graph-PIT: Generalized Permutation Invariant Training for Continuous Separation of Arbitrary Numbers of Speakers,”10.21437/interspeech.2021-1177__presented at the Interspeech, 2021, doi:10.21437/interspeech.2021-1177 .
LibreCat: /record/26770
DOI: 10.21437/interspeech.2021-1177

T. von Neumann, C. Boeddeker, K. Kinoshita, M. Delcroix, and R. Haeb-Umbach, “Speeding Up Permutation Invariant Training for Source Separation,” presented at the Speech Communication; 14th ITG Conference, Kiel, 2021.
LibreCat: /record/29173

J. Ebbers and R. Haeb-Umbach, “Self-Trained Audio Tagging and Sound Event Detection in Domestic Environments,” in Proceedings of the 6th Detection and Classification of Acoustic Scenes and Events 2021 Workshop (DCA), 2021, pp. 226–230.
LibreCat: /record/29308

J. Ebbers, M. C. Keyser, and R. Haeb-Umbach, “Adapting Sound Recognition to A New Environment Via Self-Training,” in Proceedings of the 29th European Signal Processing Conference (EUSIPCO), 2021, pp. 1135–1139.
LibreCat: /record/29306

K. J. Rohlfing et al., “Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems,”10.1109/tcds.2020.3044366__IEEE Transactions on Cognitive and Developmental Systems, vol. 13, no. 3, pp. 717–728, 2021, doi:10.1109/tcds.2020.3044366 .
LibreCat: /record/24456
DOI: 10.1109/tcds.2020.3044366

R. Haeb-Umbach, “Sprachtechnologien für Digitale Assistenten,” in Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2020, 2020, pp. 227–234.
LibreCat: /record/17763

C. Boeddeker, T. Nakatani, K. Kinoshita, and R. Haeb-Umbach, “Jointly Optimal Dereverberation and Beamforming,” in ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020.
LibreCat: /record/20695
DOI: 10.1109/icassp40776.2020.9054393

C. Boeddeker et al., “Towards a speaker diarization system for the CHiME 2020 dinner party transcription,” in Proc. CHiME 2020 Workshop on Speech Processing in Everyday Environments, 2020.
LibreCat: /record/20700

T. Nakatani, C. Boeddeker, K. Kinoshita, R. Ikeshita, M. Delcroix, and R. Haeb-Umbach, “Jointly optimal denoising, dereverberation, and source separation,”10.1109/TASLP.2020.3013118__IEEE/ACM Transactions on Audio, Speech, and Language Processing, pp. 1–1, 2020, doi:10.1109/TASLP.2020.3013118 .
LibreCat: /record/17598
DOI: 10.1109/TASLP.2020.3013118

J. Heitkaemper, D. Jakobeit, C. Boeddeker, L. Drude, and R. Haeb-Umbach, “Demystifying TasNet: A Dissecting Approach,” 2020.
LibreCat: /record/20504

S. Watanabe et al., “CHiME-6 Challenge:Tackling Multispeaker Speech Recognition for  Unsegmented Recordings,” arXiv:2004.09249. 2020.
LibreCat: /record/28263

J. Heitkaemper, J. Schmalenstroeer, and R. Haeb-Umbach, “Statistical and Neural Network Based Speech Activity Detection in Non-Stationary Acoustic Environments,” 2020.
LibreCat: /record/20505

T. von Neumann et al., “End-to-End Training of Time Domain Audio Separation and Recognition,”10.1109/ICASSP40776.2020.9053461__in ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, pp. 7004–7008, doi:10.1109/ICASSP40776.2020.9053461 .
LibreCat: /record/20762
DOI: 10.1109/ICASSP40776.2020.9053461

T. von Neumann et al., “Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source Counting, Separation and ASR,”10.21437/Interspeech.2020-2519__in Proc. Interspeech 2020, 2020, pp. 3097–3101, doi:10.21437/Interspeech.2020-2519 .
LibreCat: /record/20764
DOI: 10.21437/Interspeech.2020-2519

T. Gburrek, J. Schmalenstroeer, A. Brendel, W. Kellermann, and R. Haeb-Umbach, “Deep Neural Network based Distance Estimation for Geometry Calibration in Acoustic Sensor Network,” 2020.
LibreCat: /record/18651

K. Kinoshita, T. von Neumann, M. Delcroix, T. Nakatani, and R. Haeb-Umbach, “Multi-Path RNN for Hierarchical Modeling of Long Sequential Data and its Application to Speaker Stream Separation,”10.21437/Interspeech.2020-2388__in Proc. Interspeech 2020, 2020, pp. 2652–2656, doi:10.21437/Interspeech.2020-2388 .
LibreCat: /record/20766
DOI: 10.21437/Interspeech.2020-2388

J. Ebbers and R. Haeb-Umbach, “Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-Supervised Sound Event Detection,” 2020.
LibreCat: /record/20753

R. Haeb-Umbach, “Lektionen für Alexa \'26; Co?!,” forschung, vol. 44, no. 1, pp. 12–15, 2019.
LibreCat: /record/17762
DOI: 10.1002/fors.201970104

L. Drude, J. Heitkaemper, C. Boeddeker, and R. Haeb-Umbach, “SMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition,” ArXiv e-prints, 2019.
LibreCat: /record/19446

L. Drude, J. Heymann, and R. Haeb-Umbach, “Unsupervised training of neural mask-based beamforming,” in INTERSPEECH 2019, Graz, Austria, 2019.
LibreCat: /record/11965

L. Drude, D. Hasenklever, and R. Haeb-Umbach, “Unsupervised Training of a Deep Clustering Model for Multichannel Blind Source Separation,” in ICASSP 2019, Brighton, UK, 2019.
LibreCat: /record/12874

J. Heymann, L. Drude, R. Haeb-Umbach, K. Kinoshita, and T. Nakatani, “Joint Optimization of Neural Network-based WPE Dereverberation and Acoustic Model for Robust Online ASR,” in ICASSP 2019, Brighton, UK, 2019.
LibreCat: /record/12875

G. Kurz et al., “Directional Statistics and Filtering Using libDirectional,” in Journal of Statistical Software 89(4), 2019.
LibreCat: /record/12876

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

L. Drude, T. von Neumann, and R. Haeb-Umbach, “Deep Attractor Networks for Speaker Re-Identifikation and Blind Source Separation,” in ICASSP 2018, Calgary, Canada, 2018.
LibreCat: /record/12898

L. Drude,  Takuya  Higuchi, K. Kinoshita, T. Nakatani, and R. Haeb-Umbach, “Dual Frequency- and Block-Permutation Alignment for Deep Learning Based Block-Online Blind Source Separation,” in ICASSP 2018, Calgary, Canada, 2018.
LibreCat: /record/12900

C. Boeddeker, H. Erdogan, T. Yoshioka, and R. Haeb-Umbach, “Exploring Practical Aspects of Neural Mask-Based Beamforming for Far-Field Speech Recognition,” in ICASSP 2018, Calgary, Canada, 2018.
LibreCat: /record/12901

S. Watanabe et al., “ESPnet: End-to-End Speech Processing Toolkit,”10.21437/Interspeech.2018-1456__in INTERSPEECH 2018, Hyderabad, India, 2018, pp. 2207–2211, doi:10.21437/Interspeech.2018-1456 .
LibreCat: /record/29923
DOI: 10.21437/Interspeech.2018-1456

C. Boeddeker, J. Heitkaemper, J. Schmalenstroeer, L. Drude, J. Heymann, and R. Haeb-Umbach, “Front-End Processing for the CHiME-5 Dinner Party Scenario,” 2018.
LibreCat: /record/12899

H. Afifi, J. Schmalenstroeer, J. Ullmann, R. Haeb-Umbach, and H. Karl, “MARVELO - A Framework for Signal Processing in Wireless Acoustic Sensor Networks,” in Speech Communication; 13th ITG-Symposium, 2018, pp. 1–5.
LibreCat: /record/6859

C. Grimm, T. Breddermann, R. Farhoud, T. Fei, E. Warsitz, and R. Haeb-Umbach, “Discrimination of Stationary from Moving Targets with Recurrent Neural Networks in Automotive Radar,” 2018.
LibreCat: /record/11747

T. Glarner, P. Hanebrink, J. Ebbers, and R. Haeb-Umbach, “Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery,” 2018.
LibreCat: /record/11907

J. Schmalenstroeer and R. Haeb-Umbach, “Efficient Sampling Rate Offset Compensation - An Overlap-Save Based Approach,” 2018.
LibreCat: /record/11838

M. Kitza et al., “The RWTH/UPB System Combination for the CHiME 2018 Workshop,” 2018.
LibreCat: /record/11876

J. Ebbers, J. Heitkaemper, J. Schmalenstroeer, and R. Haeb-Umbach, “Benchmarking Neural Network Architectures for Acoustic Sensor Networks,” 2018.
LibreCat: /record/11836

J. Schmalenstroeer and R. Haeb-Umbach, “Insights into the Interplay of Sampling Rate Offsets and MVDR Beamforming,” 2018.
LibreCat: /record/11839

P. Arora and R. Haeb-Umbach, “A Study on Transfer Learning for Acoustic Event Detection in a Real Life Scenario,” in IEEE 19th International Workshop on Multimedia Signal Processing (MMSP), 2017.
LibreCat: /record/11717

C. Boeddeker, P. Hanebrink, L. Drude, J. Heymann, and R. Haeb-Umbach, On the Computation of Complex-valued Gradients with Application to Statistically Optimum Beamforming. 2017.
LibreCat: /record/11735

C. Boeddeker, P. Hanebrink, L. Drude, J. Heymann, and R. Haeb-Umbach, “Optimizing Neural-Network Supported Acoustic Beamforming by Algorithmic Differentiation,” in Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.
LibreCat: /record/11736

A. Chinaev and R. Haeb-Umbach, “A Generalized Log-Spectral Amplitude Estimator for Single-Channel Speech Enhancement,” in Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.
LibreCat: /record/11737

L. Drude and R. Haeb-Umbach, “Tight integration of spatial and spectral features for BSS with Deep Clustering embeddings,” in INTERSPEECH 2017, Stockholm, Schweden, 2017.
LibreCat: /record/11754

T. Glarner, B. Boenninghoff, O. Walter, and R. Haeb-Umbach, “Leveraging Text Data for Word Segmentation for Underresourced Languages,” in INTERSPEECH 2017, Stockholm, Schweden, 2017.
LibreCat: /record/11770

J. Heymann, L. Drude, C. Boeddeker, P. Hanebrink, and R. Haeb-Umbach, “BEAMNET: End-to-End Training of a Beamformer-Supported Multi-Channel ASR System,” in Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.
LibreCat: /record/11809

J. Heymann, L. Drude, and R. Haeb-Umbach, “A Generic Neural Acoustic Beamforming Architecture for Robust Multi-Channel Speech Processing,” Computer Speech and Language, 2017.
LibreCat: /record/11811

F. Jacob and J. Schmalenstroeer, “Building or Enclosure Termination Closing and/or Opening Apparatus, and Method for Operating a Building or Enclosure Termination.” 2017.
LibreCat: /record/12081

T. Fei, C. Grimm, R. Farhoud, T. Breddermann, E. Warsitz, and R. Haeb-Umbach, “A Novel Target Separation Algorithm Applied to The Two-Dimensional Spectrum for FMCW Automotive Radar Systems,” 2017.
LibreCat: /record/11763

C. Grimm, T. Breddermann, R. Farhoud, T. Fei, E. Warsitz, and R. Haeb-Umbach, “Hypothesis Test for the Detection of Moving Targets in Automotive Radar,” 2017.
LibreCat: /record/11772

J. Ebbers, J. Heymann, L. Drude, T. Glarner, R. Haeb-Umbach, and B. Raj, “Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery,” 2017.
LibreCat: /record/11759

J. Schmalenstroeer, J. Heymann, L. Drude, C. Boeddeker, and R. Haeb-Umbach, “Multi-Stage Coherence Drift Based Sampling Rate Synchronization for Acoustic Beamforming,” 2017.
LibreCat: /record/11895

C. Grimm, R. Farhoud, T. Fei, E. Warsitz, and R. Haeb-Umbach, “Detection of Moving Targets in Automotive Radar with Distorted Ego-Velocity Information,” 2017.
LibreCat: /record/11773

A. Chinaev and R. Haeb-Umbach, “A Priori SNR Estimation Using a Generalized Decision Directed Approach,” in INTERSPEECH 2016, San Francisco, USA, 2016.
LibreCat: /record/11738

A. Chinaev, J. Heitkaemper, and R. Haeb-Umbach, “A Priori SNR Estimation Using Weibull Mixture Model,” in 12. ITG Fachtagung Sprachkommunikation (ITG 2016), 2016.
LibreCat: /record/11743

A. Chinaev, J. Heymann, L. Drude, and R. Haeb-Umbach, “Noise-Presence-Probability-Based Noise PSD Estimation by Using DNNs,” in 12. ITG Fachtagung Sprachkommunikation (ITG 2016), 2016.
LibreCat: /record/11744

L. Drude, C. Boeddeker, and R. Haeb-Umbach, “Blind Speech Separation based on Complex Spherical k-Mode Clustering,” in Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2016.
LibreCat: /record/11751

L. Drude, B. Raj, and R. Haeb-Umbach, “On the appropriateness of complex-valued neural networks for speech enhancement,” in INTERSPEECH 2016, San Francisco, USA, 2016.
LibreCat: /record/11756