C. Boeddeker, A. S. Subramanian, G. Wichern, R. Haeb-Umbach, and J. Le Roux, “TS-SEP: Joint Diarization and Separation Conditioned on Estimated Speaker Embeddings,”10.1109/taslp.2024.3350887__IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 32, pp. 1185–1197, 2024, doi:10.1109/taslp.2024.3350887 .
LibreCat: /record/52958
DOI: 10.1109/taslp.2024.3350887

T. Cord-Landwehr, C. Boeddeker, C. Zoril, R. Doddipatla, and R. Haeb-Umbach, “Geodesic Interpolation of Frame-Wise Speaker Embeddings for the Diarization of Meeting Scenarios,”10.1109/icassp48485.2024.10445911__presented at the 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Seoul, 2024, doi:10.1109/icassp48485.2024.10445911 .
LibreCat: /record/53659
DOI: 10.1109/icassp48485.2024.10445911

T. Gburrek, J. Schmalenstroeer, and R. Haeb-Umbach, “On the Integration of Sampling Rate Synchronization and Acoustic Beamforming,” presented at the European Signal Processing Conference (EUSIPCO), Helsinki, 2023.
LibreCat: /record/48269

T. Cord-Landwehr, C. Boeddeker, C. Zoril, R. Doddipatla, and R. Haeb-Umbach, “Frame-Wise and Overlap-Robust Speaker Embeddings for Meeting Diarization,”10.1109/icassp49357.2023.10095370__presented at the 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Rhodes, 2023, doi:10.1109/icassp49357.2023.10095370 .
LibreCat: /record/47128
DOI: 10.1109/icassp49357.2023.10095370

J. Schmalenstroeer, T. Gburrek, and R. Haeb-Umbach, “LibriWASN: A Data Set for Meeting Separation, Diarization, and Recognition with Asynchronous Recording Devices,” presented at the ITG Conference on Speech Communication, Aachen, 2023.
LibreCat: /record/48270

T. Cord-Landwehr, C. Boeddeker, C. Zoril, R. Doddipatla, and R. Haeb-Umbach, “A Teacher-Student Approach for Extracting Informative Speaker Embeddings From Speech Mixtures,”10.21437/interspeech.2023-1379__2023, doi:10.21437/interspeech.2023-1379 .
LibreCat: /record/47129
DOI: 10.21437/interspeech.2023-1379

F. Rautenberg, M. Kuhlmann, J. Wiechmann, F. Seebauer, P. Wagner, and R. Haeb-Umbach, “On Feature Importance and Interpretability of Speaker Representations,” presented at the ITG Conference on Speech Communication, Aachen, 2023.
LibreCat: /record/48355
arXiv: 2310.12599

J. Wiechmann, F. Rautenberg, P. Wagner, and R. Haeb-Umbach, “Explaining voice characteristics to novice voice practitioners-How successful is it?,” 2023.
LibreCat: /record/48410

R. Aralikatti, C. Boeddeker, G. Wichern, A. Subramanian, and J. Le Roux, “Reverberation as Supervision For Speech Separation,”10.1109/icassp49357.2023.10095022__2023, doi:10.1109/icassp49357.2023.10095022 .
LibreCat: /record/48391
DOI: 10.1109/icassp49357.2023.10095022

S. Berger, P. Vieting, C. Boeddeker, R. Schlüter, and R. Haeb-Umbach, “Mixture Encoder for Joint Speech Separation and Recognition,”10.21437/interspeech.2023-1815__2023, doi:10.21437/interspeech.2023-1815 .
LibreCat: /record/48390
DOI: 10.21437/interspeech.2023-1815

F. Seebauer, M. Kuhlmann, R. Haeb-Umbach, and P. Wagner, “Re-examining the quality dimensions of synthetic speech,” 2023.
LibreCat: /record/46069

T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, and R. Haeb-Umbach, “Segment-Less Continuous Speech Separation of Meetings: Training and Evaluation Criteria,”10.1109/taslp.2022.3228629__IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 31, pp. 576–589, 2023, doi:10.1109/taslp.2022.3228629 .
LibreCat: /record/35602
DOI: 10.1109/taslp.2022.3228629

T. von Neumann, C. Boeddeker, K. Kinoshita, M. Delcroix, and R. Haeb-Umbach, “On Word Error Rate Definitions and Their Efficient Computation for Multi-Speaker Speech Recognition Systems,”10.1109/icassp49357.2023.10094784__2023, doi:10.1109/icassp49357.2023.10094784 .
LibreCat: /record/48281
DOI: 10.1109/icassp49357.2023.10094784

T. von Neumann, C. Boeddeker, M. Delcroix, and R. Haeb-Umbach, “MeetEval: A Toolkit for Computation of Word Error Rates for Meeting Transcription Systems,” presented at the CHiME 2023 Workshop on Speech Processing in Everyday Environments, Dublin, 2023.
LibreCat: /record/48275

T. Gburrek, J. Schmalenstroeer, and R. Haeb-Umbach, “Spatial Diarization for Meeting Transcription with Ad-Hoc Acoustic Sensor Networks,” presented at the 57th Asilomar Conference on Signals, Systems, and Computers, 2023.
LibreCat: /record/49109

J. Ebbers, R. Haeb-Umbach, and R. Serizel, “Post-Processing Independent Evaluation of Sound Event Detection Systems,” in Proceedings of the 8th Detection and Classification of Acoustic Scenes and Events 2023 Workshop (DCA), 2023, pp. 36–40.
LibreCat: /record/49111

F. Rautenberg et al., “Speech Disentanglement for Analysis and Modification of Acoustic and Perceptual Speaker Characteristics,” in Fortschritte der Akustik - DAGA 2023, Hamburg, 2023, pp. 1409–1412.
LibreCat: /record/44849

W. Zhang, X. Chang, C. Boeddeker, T. Nakatani, S. Watanabe, and Y. Qian, “End-to-End Dereverberation, Beamforming, and Speech Recognition in A Cocktail Party,”10.1109/TASLP.2022.3209942__IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2022, doi:10.1109/TASLP.2022.3209942 .
LibreCat: /record/33669
DOI: 10.1109/TASLP.2022.3209942

C. Boeddeker, T. Cord-Landwehr, T. von Neumann, and R. Haeb-Umbach, “An Initialization Scheme for Meeting Separation with Spatial Mixture Models,”10.21437/interspeech.2022-10929__2022, doi:10.21437/interspeech.2022-10929 .
LibreCat: /record/33954
DOI: 10.21437/interspeech.2022-10929

J. Heitkämper, J. Schmalenstroeer, and R. Haeb-Umbach, “Neural Network Based Carrier Frequency Offset Estimation From Speech Transmitted Over High Frequency Channels,” presented at the 30th European Signal Processing Conference (EUSIPCO), Belgrad.
LibreCat: /record/33471

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

T. Glarner, M. Mahdi Momenzadeh, L. Drude, and R. Haeb-Umbach, “Factor Graph Decoding for Speech Presence Probability Estimation,” in 12. ITG Fachtagung Sprachkommunikation (ITG 2016), 2016.
LibreCat: /record/11771

J. Heymann, L. Drude, and R. Haeb-Umbach, “Neural Network Based Spectral Mask Estimation for Acoustic Beamforming,” in Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2016.
LibreCat: /record/11812

F. Jacob and R. Haeb-Umbach, “On the Bias of Direction of Arrival Estimation Using Linear Microphone Arrays,” in 12. ITG Fachtagung Sprachkommunikation (ITG 2016), 2016.
LibreCat: /record/11829

J. Heymann, L. Drude, and R. Haeb-Umbach, “Wide Residual BLSTM Network with Discriminative Speaker Adaptation for Robust Speech Recognition,” in Computer Speech and Language, 2016.
LibreCat: /record/11834

K. Kinoshita et al., “A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research,” EURASIP Journal on Advances in Signal Processing, 2016.
LibreCat: /record/11840

A. Plinge, F. Jacob, R. Haeb-Umbach, and G. A. Fink, “Acoustic Microphone Geometry Calibration: An overview and experimental evaluation of state-of-the-art algorithms,” IEEE Signal Processing Magazine, vol. 33, no. 4, pp. 14–29, 2016.
LibreCat: /record/11886
DOI: 10.1109/MSP.2016.2555198

T. Menne et al., “The RWTH/UPB/FORTH System Combination for the 4th CHiME Challenge Evaluation,” in Computer Speech and Language, 2016.
LibreCat: /record/11908

O. Walter and R. Haeb-Umbach, “Unsupervised Word Discovery from Speech using Bayesian Hierarchical Models,” in 38th German Conference on Pattern Recognition (GCPR 2016), 2016.
LibreCat: /record/11920

J. Schmalenstroeer and R. Haeb-Umbach, “Investigations into Bluetooth Low Energy Localization Precision Limits,” 2016.
LibreCat: /record/11890

A. Chinaev and R. Haeb-Umbach, “On Optimal Smoothing in Minimum Statistics Based Noise Tracking,” in Interspeech 2015, 2015, pp. 1785–1789.
LibreCat: /record/11739

V. Despotovic, O. Walter, and R. Haeb-Umbach, “Semantic Analysis of Spoken Input using Markov Logic Networks,” in INTERSPEECH 2015, 2015.
LibreCat: /record/11748

L. Drude, F. Jacob, and R. Haeb-Umbach, “DOA-Estimation based on a Complex Watson Kernel Method,” in 23th European Signal Processing Conference (EUSIPCO 2015), 2015.
LibreCat: /record/11755

J. Heymann, L. Drude, A. Chinaev, and R. Haeb-Umbach, “BLSTM supported GEV Beamformer Front-End for the 3RD CHiME Challenge,” in Automatic Speech Recognition and Understanding Workshop (ASRU 2015), 2015.
LibreCat: /record/11810

J. Heymann, R. Haeb-Umbach, P. Golik, and R. Schlueter, “Unsupervised adaptation of a denoising autoencoder by Bayesian Feature Enhancement for reverberant asr under mismatch conditions,” in Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on, 2015, pp. 5053–5057.
LibreCat: /record/11813
DOI: 10.1109/ICASSP.2015.7178933

F. Jacob and R. Haeb-Umbach, “Absolute Geometry Calibration of Distributed Microphone Arrays in an Audio-Visual Sensor Network,” ArXiv e-prints, 2015.
LibreCat: /record/11830

J. Li, L. Deng, R. Haeb-Umbach, and Y. Gong, Robust Automatic Speech Recognition. Elsevier, 2015.
LibreCat: /record/11868

E. Marchi et al., “Typicality and Emotion in the Voice of Children with Autism Spectrum Condition: Evidence Across Three Languages,” in INTERSPEECH 2015, 2015.
LibreCat: /record/11875

O. Walter, L. Drude, and R. Haeb-Umbach, “Source Counting in Speech Mixtures by Nonparametric Bayesian Estimation of an infinite Gaussian Mixture Model,” in 40th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2015), 2015.
LibreCat: /record/11919

O. Walter, R. Haeb-Umbach, B. Mokbel, B. Paassen, and B. Hammer, “Autonomous Learning of Representations,” KI - Kuenstliche Intelligenz, pp. 1–13, 2015.
LibreCat: /record/11922
DOI: http://dx.doi.org/10.1007/s13218-015-0372-1

O. Walter, R. Haeb-Umbach, J. Strunk, and N. P. Himmelmann, Lexicon Discovery for Language Preservation using Unsupervised Word Segmentation with Pitman-Yor Language Models (FGNT-2015-01). 2015.
LibreCat: /record/11923

M. K. Hoang, J. Schmalenstroeer, and R. Haeb-Umbach, “Aligning training models with smartphone properties in WiFi fingerprinting based indoor localization,” 2015.
LibreCat: /record/11874

A. Chinaev, M. Puels, and R. Haeb-Umbach, “Spectral Noise Tracking for Improved Nonstationary Noise Robust ASR,” in 11. ITG Fachtagung Sprachkommunikation (ITG 2014), 2014.
LibreCat: /record/11746

L. Drude, A. Chinaev, D. H. Tran Vu, and R. Haeb-Umbach, “Source Counting in Speech Mixtures Using a Variational EM Approach for Complexwatson Mixture Models,” in 39th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), 2014.
LibreCat: /record/11752

L. Drude, A. Chinaev, D. H. Tran Vu, and R. Haeb-Umbach, “Towards Online Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models,” in 14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014), 2014, pp. 213–217.
LibreCat: /record/11753

J. Heymann, O. Walter, R. Haeb-Umbach, and B. Raj, “Iterative Bayesian Word Segmentation for Unspuervised Vocabulary Discovery from Phoneme Lattices,” in 39th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), 2014.
LibreCat: /record/11814

F. Jacob and R. Haeb-Umbach, “Coordinate Mapping Between an Acoustic and Visual Sensor Network in the Shape Domain for a Joint Self-Calibrating Speaker Tracking,” in 11. ITG Fachtagung Sprachkommunikation (ITG 2014), 2014.
LibreCat: /record/11831

V. Leutnant, A. Krueger, and R. Haeb-Umbach, “A New Observation Model in the Logarithmic Mel Power Spectral Domain for the Automatic Recognition of Noisy Reverberant Speech,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 22, no. 1, pp. 95–109, 2014.
LibreCat: /record/11861
DOI: 10.1109/TASLP.2013.2285480

J. Li, L. Deng, Y. Gong, and R. Haeb-Umbach, “An Overview of Noise-Robust Automatic Speech Recognition,” IEEE Transactions on Audio, Speech and Language Processing, vol. 22, no. 4, pp. 745–777, 2014.
LibreCat: /record/11867
DOI: 10.1109/TASLP.2014.2304637

O. Walter, V. Despotovic, R. Haeb-Umbach, J. Gemmeke, B. Ons, and H. Van hamme, “An Evaluation of Unsupervised Acoustic Model Training for a Dysarthric Speech Interface,” in INTERSPEECH 2014, 2014.
LibreCat: /record/11918

J. Schmalenstroeer, P. Jebramcik, and R. Haeb-Umbach, “A combined hardware-software approach for acoustic sensor network synchronization ,”http://dx.doi.org/10.1016/j.sigpro.2014.06.030__Signal Processing, no. 0, p., 2014, doi:http://dx.doi.org/10.1016/j.sigpro.2014.06.030 .
LibreCat: /record/11898
DOI: http://dx.doi.org/10.1016/j.sigpro.2014.06.030

J. Schmalenstroeer, P. Jebramcik, and R. Haeb-Umbach, “A Gossiping Approach to Sampling Clock Synchronization in Wireless Acoustic Sensor Networks,” 2014.
LibreCat: /record/11897

J. Schmalenstroeer, W. Zhao, and R. Haeb-Umbach, “Online Observation Error Model Estimation for Acoustic Sensor Network Synchronization,” 2014.
LibreCat: /record/11903

A. H. Abdelaziz, S. Zeiler, D. Kolossa, V. Leutnant, and R. Haeb-Umbach, “GMM-based significance decoding,” in Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on, 2013, pp. 6827–6831.
LibreCat: /record/11716
DOI: 10.1109/ICASSP.2013.6638984

A. Chinaev and R. Haeb-Umbach, “MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations,” in 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 3352–3356.
LibreCat: /record/11740
DOI: 10.1109/ICASSP.2013.6638279

A. Chinaev, R. Haeb-Umbach, J. Taghia, and R. Martin, “Improved Single-Channel Nonstationary Noise Tracking by an Optimized MAP-based Postprocessor,” in 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 7477–7481.
LibreCat: /record/11742
DOI: 10.1109/ICASSP.2013.6639116

G. Enzner, D. Schmid, and R. Haeb-Umbach, “On the Acoustic Channel Identification in Multi-Microphone Systems via Adaptive Blind Signal Enhancement Techniques,” in 21th European Signal Processing Conference (EUSIPCO 2013), 2013.
LibreCat: /record/11762

J. Heymann, O. Walter, R. Haeb-Umbach, and B. Raj, “Unsupervised Word Segmentation from Noisy Input,” in Automatic Speech Recognition and Understanding Workshop (ASRU 2013), 2013.
LibreCat: /record/11815

M. K. Hoang and R. Haeb-Umbach, “Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning,” in 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), 2013, pp. 3721–3725.
LibreCat: /record/11816
DOI: 10.1109/ICASSP.2013.6638353

K. Kinoshita et al., “The reverb challenge: a common evaluation framework for dereverberation and recognition of reverberant speech,” in  IEEE Workshop on Applications of Signal Processing to Audio and Acoustics , 2013, pp. 22–23.
LibreCat: /record/11841

V. Leutnant, A. Krueger, and R. Haeb-Umbach, “Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 21, no. 8, pp. 1640–1652, 2013.
LibreCat: /record/11862
DOI: 10.1109/TASL.2013.2258013

D. H. Tran Vu and R. Haeb-Umbach, “Blind Speech Separation Exploiting Temporal and Spectral Correlations Using Turbo Decoding of 2D-HMMs,” in 21th European Signal Processing Conference (EUSIPCO 2013), 2013.
LibreCat: /record/11909

D. H. T. Vu and R. Haeb-Umbach, “Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation,” in 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 863–867.
LibreCat: /record/11917
DOI: 10.1109/ICASSP.2013.6637771

O. Walter, R. Haeb-Umbach, S. Chaudhuri, and B. Raj, “Unsupervised Word Discovery from Phonetic Input Using Nested Pitman-Yor Language Modeling,” in IEEE International Conference on Robotics and Automation (ICRA 2013), 2013.
LibreCat: /record/11921

O. Walter, T. Korthals, R. Haeb-Umbach, and B. Raj, “Hierarchical System for Word Discovery Exploiting DTW-Based Initialization,” in Automatic Speech Recognition and Understanding Workshop (ASRU 2013), 2013.
LibreCat: /record/11924

O. Walter, J. Schmalenstroeer, and R. Haeb-Umbach, A Novel Initialization Method for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01). 2013.
LibreCat: /record/11926

F. Jacob, J. Schmalenstroeer, and R. Haeb-Umbach, “DoA-Based Microphone Array Position Self-Calibration Using Circular Statistic,”10.1109/ICASSP.2013.6637620__in 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), 2013, pp. 116–120, doi:10.1109/ICASSP.2013.6637620 .
LibreCat: /record/11832
DOI: 10.1109/ICASSP.2013.6637620

J. Schmalenstroeer and R. Haeb-Umbach, “Sampling Rate Synchronisation in Acoustic Sensor Networks with a Pre-Trained Clock Skew Error Model,” 2013.
LibreCat: /record/11891

M. K. Hoang, S. Schmitz, C. Drueke, D. H. T. Vu, J. Schmalenstroeer, and R. Haeb-Umbach, “Server based indoor navigation using RSSI and inertial sensor information,”10.1109/WPNC.2013.6533263__in Positioning Navigation and Communication (WPNC), 2013 10th Workshop on, 2013, pp. 1–6, doi:10.1109/WPNC.2013.6533263 .
LibreCat: /record/11818
DOI: 10.1109/WPNC.2013.6533263

M. K. Hoang, J. Schmalenstroeer, C. Drueke, D. H. Tran Vu, and R. Haeb-Umbach, “A Hidden Markov Model for Indoor User Tracking Based on WiFi Fingerprinting and Step Detection,” 2013.
LibreCat: /record/11817

A. Chinaev and R. Haeb-Umbach, “Quality Analysis and Optimization of the MAP-based Noise Power Spectral Density Tracker,” in Speech Communication; 10. ITG Symposium; Proceedings., 2012.
LibreCat: /record/11741

A. Chinaev, A. Krueger, D. H. Tran Vu, and R. Haeb-Umbach, “Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor,” in 37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012), 2012.
LibreCat: /record/11745

A. Krueger and R. Haeb-Umbach, “Reverberant Speech Recognition,” in Techniques for Noise Robustness in Automatic Speech Recognition, Wiley, 2012.
LibreCat: /record/11844

A. Krueger, O. Walter, V. Leutnant, and R. Haeb-Umbach, “Bayesian Feature Enhancement for ASR of Noisy Reverberant Real-World Data,” in Proc. Interspeech, 2012.
LibreCat: /record/11849

V. Leutnant, A. Krueger, and R. Haeb-Umbach, “Investigations Into a Statistical Observation Model for Logarithmic Mel Power Spectral Density Features of Noisy Reverberant Speech,” Speech Communication; 10. ITG Symposium; Proceedings of, pp. 1–4, 2012.
LibreCat: /record/11863

V. Leutnant, A. Krueger, and R. Haeb-Umbach, “A Statistical Observation Model For Noisy Reverberant Speech Features and its Application to Robust ASR,” in Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference on, 2012.
LibreCat: /record/11864

V. Leutnant, A. Krueger, and R. Haeb-Umbach, Derivation of the Power Compensation Constant in the Observation Model for Reverberant Speech in the Logarithmic Mel Power Spectral Domain. 2012.
LibreCat: /record/11865

D. H. Tran Vu and R. Haeb-Umbach, “Exploiting Temporal Correlations in Joint Multichannel Speech Separation and Noise Suppression using Hidden Markov Models,” in International Workshop on Acoustic Signal Enhancement (IWAEN12), 2012.
LibreCat: /record/11910

F. Jacob, J. Schmalenstroeer, and R. Haeb-Umbach, “Microphone Array Position Self-Calibration from Reverberant Speech Input,” 2012.
LibreCat: /record/11833

O. Walter, J. Schmalenstroeer, A. Engler, and R. Haeb-Umbach, “Smartphone-Based Sensor Fusion for Improved Vehicular Navigation,” 2012.
LibreCat: /record/11925

M. Bevermeier, S. Flanke, R. Haeb-Umbach, and J. Stehr, “A Platform for efficient Supply Chain Management Support in Logistics,” in International Workshop on Intelligent Transportation (WIT 2011), 2011.
LibreCat: /record/11721

R. Haeb-Umbach, “Uncertainty Decoding and Conditional Bayesian Estimation,” in Robust Speech Recognition of Uncertain or Missing Data, R. Haeb-Umbach and D. Kolossa, Eds. Springer, 2011.
LibreCat: /record/11774

R. Haeb-Umbach, “Können Computer sprechen und hören, sollen sie es überhaupt können? Sprachverarbeitung und ambiente Intelligenz,” in Baustelle Informationsgesellschaft und Universität heute, Ferdinand Schoeningh Verlag, Paderborn, 2011.
LibreCat: /record/11775

T. Herbig, F. Gerl, W. Minker, and R. Haeb-Umbach, “Adaptive Systems for Unsupervised Speaker Tracking and Speech Recognition,” Evolving Systems, vol. 2, no. 3, pp. 199–214, 2011.
LibreCat: /record/11807

A. Krueger and R. Haeb-Umbach, “A Model-Based Approach to Joint Compensation of Noise and Reverberation for Speech Recognition,” in Robust Speech Recognition of Uncertain or Missing Data, R. Haeb-Umbach and D. Kolossa, Eds. Springer, 2011.
LibreCat: /record/11843

A. Krueger and R. Haeb-Umbach, “MAP-based estimation of the parameters of non-stationary Gaussian processes from noisy observations,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 2011, pp. 3596–3599.
LibreCat: /record/11845
DOI: 10.1109/ICASSP.2011.5946256

A. Krueger, E. Warsitz, and R. Haeb-Umbach, “Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 19, no. 1, pp. 206–219, 2011.
LibreCat: /record/11850
DOI: 10.1109/TASL.2010.2047324

V. Leutnant and R. Haeb-Umbach, “Conditional Bayesian Estimation Employing a Phase-Sensitive Observation Model for Noise Robust Speech Recognition,” in Robust Speech Recognition of Uncertain or Missing Data, R. Haeb-Umbach and D. Kolossa, Eds. Springer, 2011.
LibreCat: /record/11856

V. Leutnant, A. Krueger, and R. Haeb-Umbach, “A versatile Gaussian splitting approach to non-linear state estimation and its application to noise-robust ASR,” in Interspeech 2011, 2011.
LibreCat: /record/11866

D. H. Tran Vu and R. Haeb-Umbach, “On Initial Seed Selection for Frequency Domain Blind Speech Separation,” in Interspeech 2011, 2011.
LibreCat: /record/11911

D. Kolossa and R. Haeb-Umbach, Eds., Robust Speech Recognition of Uncertain or Missing Data --- Theory and Applications. Springer, 2011.
LibreCat: /record/11945

J. Schmalenstroeer, M. Bartek, and R. Haeb-Umbach, “Unsupervised learning of acoustic events using dynamic time warping and hierarchical K-means++ clustering,” 2011.
LibreCat: /record/11889

J. Schmalenstroeer, F. Jacob, R. Haeb-Umbach, M. Hennecke, and G. A. Fink, “Unsupervised Geometry Calibration of Acoustic Sensor Networks Using Source Correspondences,” 2011.
LibreCat: /record/11896

J. Schmalenstroeer, M. Bartek, and R. Haeb-Umbach, “Investigations into Features for Robust Classification into Broad Acoustic Categories,” 2011.
LibreCat: /record/9456

M. Bevermeier, O. Walter, S. Peschke, and R. Haeb-Umbach, “Barometric height estimation combined with map-matching in a loosely-coupled Kalman-filter,” in 7th Workshop on Positioning Navigation and Communication (WPNC 2010), 2010, pp. 128–134.
LibreCat: /record/11726
DOI: 10.1109/WPNC.2010.5650745

A. Krueger and R. Haeb-Umbach, “Model-Based Feature Enhancement for Reverberant Speech Recognition,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 18, no. 7, pp. 1692–1707, 2010.
LibreCat: /record/11846
DOI: 10.1109/TASL.2010.2049684

V. Leutnant and R. Haeb-Umbach, “Options for Modelling Temporal Statistical Dependencies in an Acoustic Model for ASR,” in 36. Deutsche Jahrestagung fuer Akustik (DAGA 2010), 2010.
LibreCat: /record/11857

V. Leutnant and R. Haeb-Umbach, “On the Exploitation of Hidden Markov Models and Linear Dynamic Models in a Hybrid Decoder Architecture for Continuous Speech Recognition,” in Interspeech 2010, 2010.
LibreCat: /record/11858

B. Raj, K. W. Wilson, A. Krueger, and R. Haeb-Umbach, “Ungrounded Independent Non-Negative Factor Analysis,” in Interspeech 2010, 2010.
LibreCat: /record/11887

D. H. Tran Vu and R. Haeb-Umbach, “An EM Approach to Integrated Multichannel Speech Separation and Noise Suppression,” in International Workshop on Acoustic Echo and Noise Control (IWAENC 2010), 2010.
LibreCat: /record/11912

D. H. Tran Vu and R. Haeb-Umbach, “Blind speech separation employing directional statistics in an Expectation Maximization framework,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), 2010, pp. 241–244.
LibreCat: /record/11913
DOI: 10.1109/ICASSP.2010.5495994