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

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

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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

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

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.

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

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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

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

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

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.

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.

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.

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

J. Li, L. Deng, R. Haeb-Umbach, and Y. Gong, Robust Automatic Speech Recognition. Elsevier, 2015.

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

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.

O. Walter, R. Haeb-Umbach, B. Mokbel, B. Paassen, and B. Hammer, “Autonomous Learning of Representations,” KI - Kuenstliche Intelligenz, pp. 1–13, 2015.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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 .

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

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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 .

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

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 .

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.

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.

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.

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

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.

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.

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.

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.

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.

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

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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

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

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

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

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.

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.

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.

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.

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

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.