von Neumann, T., Boeddeker, C., Drude, L., Kinoshita, K., Delcroix, M., Nakatani, T., &; Haeb-Umbach, R. (2020). Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source Counting, Separation and ASR. Proc. Interspeech 2020, 3097–3101.https://doi.org/10.21437/Interspeech.2020-2519 

Gburrek, T., Schmalenstroeer, J., Brendel, A., Kellermann, W., &; Haeb-Umbach, R. (2020). Deep Neural Network based Distance Estimation for Geometry Calibration in Acoustic Sensor Network. European Signal Processing Conference (EUSIPCO).

Kinoshita, K., von Neumann, T., Delcroix, M., Nakatani, T., &; Haeb-Umbach, R. (2020). Multi-Path RNN for Hierarchical Modeling of Long Sequential Data and its Application to Speaker Stream Separation. Proc. Interspeech 2020, 2652–2656.https://doi.org/10.21437/Interspeech.2020-2388 

Ebbers, J., &; Haeb-Umbach, R. (2020). Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-Supervised Sound Event Detection. Proceedings of the Detection and Classification of Acoustic Scenes and Events 2020 Workshop (DCA).

Haeb-Umbach, R. (2019). Lektionen für Alexa \'26; Co?! Forschung, 44(1), 12–15.https://doi.org/10.1002/fors.201970104 

Drude, L., Heitkaemper, J., Boeddeker, C., &; Haeb-Umbach, R. (2019). SMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition. ArXiv E-Prints.

Drude, L., Heymann, J., &; Haeb-Umbach, R. (2019). Unsupervised training of neural mask-based beamforming. In INTERSPEECH 2019, Graz, Austria.

Drude, L., Hasenklever, D., &; Haeb-Umbach, R. (2019). Unsupervised Training of a Deep Clustering Model for Multichannel Blind Source Separation. In ICASSP 2019, Brighton, UK.

Heymann, J., Drude, L., Haeb-Umbach, R., Kinoshita, K., &; Nakatani, T. (2019). Joint Optimization of Neural Network-based WPE Dereverberation and Acoustic Model for Robust Online ASR. In ICASSP 2019, Brighton, UK.

Kurz, G., Gilitschenski, I., Pfaff, F., Drude, L., Hanebeck, U. D., Haeb-Umbach, R., &; Siegwart, R. Y. (2019). Directional Statistics and Filtering Using libDirectional. In Journal of Statistical Software 89(4).

Drude, L., &; Haeb-Umbach, R. (2019). Integration of Neural Networks and Probabilistic Spatial Models for Acoustic Blind Source Separation. IEEE Journal of Selected Topics in Signal Processing.https://doi.org/10.1109/JSTSP.2019.2912565 

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

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

Heitkaemper, J., Feher, T., Freitag, M., &; Haeb-Umbach, R. (2019). A Study on Online Source Extraction in the Presence of Changing Speaker Positions. In International Conference on Statistical Language and Speech Processing 2019, Ljubljana, Slovenia.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Drude, L., von Neumann, T., &; Haeb-Umbach, R. (2018). Deep Attractor Networks for Speaker Re-Identifikation and Blind Source Separation. In ICASSP 2018, Calgary, Canada.

Drude, L., Higuchi,  Takuya , Kinoshita, K., Nakatani, T., &; Haeb-Umbach, R. (2018). Dual Frequency- and Block-Permutation Alignment for Deep Learning Based Block-Online Blind Source Separation. In ICASSP 2018, Calgary, Canada.

Boeddeker, C., Erdogan, H., Yoshioka, T., &; Haeb-Umbach, R. (2018). Exploring Practical Aspects of Neural Mask-Based Beamforming for Far-Field Speech Recognition. In ICASSP 2018, Calgary, Canada.

Watanabe, S., Hori, T., Karita, S., Hayashi, T., Nishitoba, J., Unno, Y., Enrique Yalta Soplin, N., Heymann, J., Wiesner, M., Chen, N., Renduchintala, A., &; Ochiai, T. (2018). ESPnet: End-to-End Speech Processing Toolkit. INTERSPEECH 2018, Hyderabad, India, 2207–2211.https://doi.org/10.21437/Interspeech.2018-1456 

Boeddeker, C., Heitkaemper, J., Schmalenstroeer, J., Drude, L., Heymann, J., &; Haeb-Umbach, R. (2018). Front-End Processing for the CHiME-5 Dinner Party Scenario. Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India.

Afifi, H., Schmalenstroeer, J., Ullmann, J., Haeb-Umbach, R., &; Karl, H. (2018). MARVELO - A Framework for Signal Processing in Wireless Acoustic Sensor Networks. Speech Communication; 13th ITG-Symposium, 1–5.

Grimm, C., Breddermann, T., Farhoud, R., Fei, T., Warsitz, E., &; Haeb-Umbach, R. (2018). Discrimination of Stationary from Moving Targets with Recurrent Neural Networks in Automotive Radar. International Conference on Microwaves for Intelligent Mobility (ICMIM) 2018.

Glarner, T., Hanebrink, P., Ebbers, J., &; Haeb-Umbach, R. (2018). Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery. INTERSPEECH 2018, Hyderabad, India.

Schmalenstroeer, J., &; Haeb-Umbach, R. (2018). Efficient Sampling Rate Offset Compensation - An Overlap-Save Based Approach. 26th European Signal Processing Conference (EUSIPCO 2018).

Kitza, M., Michel, W., Boeddeker, C., Heitkaemper, J., Menne, T., Schlüter, R., Ney, H., Schmalenstroeer, J., Drude, L., Heymann, J., &; Haeb-Umbach, R. (2018). The RWTH/UPB System Combination for the CHiME 2018 Workshop. Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India.

Ebbers, J., Heitkaemper, J., Schmalenstroeer, J., &; Haeb-Umbach, R. (2018). Benchmarking Neural Network Architectures for Acoustic Sensor Networks. ITG 2018, Oldenburg, Germany.

Schmalenstroeer, J., &; Haeb-Umbach, R. (2018). Insights into the Interplay of Sampling Rate Offsets and MVDR Beamforming. ITG 2018, Oldenburg, Germany.

Arora, P., &; Haeb-Umbach, R. (2017). A Study on Transfer Learning for Acoustic Event Detection in a Real Life Scenario. In IEEE 19th International Workshop on Multimedia Signal Processing (MMSP).

Boeddeker, C., Hanebrink, P., Drude, L., Heymann, J., &; Haeb-Umbach, R. (2017). On the Computation of Complex-valued Gradients with Application to Statistically Optimum Beamforming.

Boeddeker, C., Hanebrink, P., Drude, L., Heymann, J., &; Haeb-Umbach, R. (2017). Optimizing Neural-Network Supported Acoustic Beamforming by Algorithmic Differentiation. In Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP).

Chinaev, A., &; Haeb-Umbach, R. (2017). A Generalized Log-Spectral Amplitude Estimator for Single-Channel Speech Enhancement. In Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP).

Drude, L., &; Haeb-Umbach, R. (2017). Tight integration of spatial and spectral features for BSS with Deep Clustering embeddings. In INTERSPEECH 2017, Stockholm, Schweden.

Glarner, T., Boenninghoff, B., Walter, O., &; Haeb-Umbach, R. (2017). Leveraging Text Data for Word Segmentation for Underresourced Languages. In INTERSPEECH 2017, Stockholm, Schweden.

Heymann, J., Drude, L., Boeddeker, C., Hanebrink, P., &; Haeb-Umbach, R. (2017). 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).

Heymann, J., Drude, L., &; Haeb-Umbach, R. (2017). A Generic Neural Acoustic Beamforming Architecture for Robust Multi-Channel Speech Processing. Computer Speech and Language.

Jacob, F., &; Schmalenstroeer, J. (2017). Building or Enclosure Termination Closing and/or Opening Apparatus, and Method for Operating a Building or Enclosure Termination.

Fei, T., Grimm, C., Farhoud, R., Breddermann, T., Warsitz, E., &; Haeb-Umbach, R. (2017). A Novel Target Separation Algorithm Applied to The Two-Dimensional Spectrum for FMCW Automotive Radar Systems. IEEE International Conference on Microwave, Communications, Anthenas and Electronic Systems.

Grimm, C., Breddermann, T., Farhoud, R., Fei, T., Warsitz, E., &; Haeb-Umbach, R. (2017). Hypothesis Test for the Detection of Moving Targets in Automotive Radar. IEEE International Conference on Microwave, Communications, Anthenas and Electronic Systems (COMCAS).

Ebbers, J., Heymann, J., Drude, L., Glarner, T., Haeb-Umbach, R., &; Raj, B. (2017). Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery. INTERSPEECH 2017, Stockholm, Schweden.

Schmalenstroeer, J., Heymann, J., Drude, L., Boeddeker, C., &; Haeb-Umbach, R. (2017). Multi-Stage Coherence Drift Based Sampling Rate Synchronization for Acoustic Beamforming. IEEE 19th International Workshop on Multimedia Signal Processing (MMSP).

Grimm, C., Farhoud, R., Fei, T., Warsitz, E., &; Haeb-Umbach, R. (2017). Detection of Moving Targets in Automotive Radar with Distorted Ego-Velocity Information. IEEE Microwaves, Radar and Remote Sensing Symposium (MRRS).

Chinaev, A., &; Haeb-Umbach, R. (2016). A Priori SNR Estimation Using a Generalized Decision Directed Approach. In INTERSPEECH 2016, San Francisco, USA.

Chinaev, A., Heitkaemper, J., &; Haeb-Umbach, R. (2016). A Priori SNR Estimation Using Weibull Mixture Model. In 12. ITG Fachtagung Sprachkommunikation (ITG 2016).

Chinaev, A., Heymann, J., Drude, L., &; Haeb-Umbach, R. (2016). Noise-Presence-Probability-Based Noise PSD Estimation by Using DNNs. In 12. ITG Fachtagung Sprachkommunikation (ITG 2016).

Drude, L., Boeddeker, C., &; Haeb-Umbach, R. (2016). Blind Speech Separation based on Complex Spherical k-Mode Clustering. In Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP).

Drude, L., Raj, B., &; Haeb-Umbach, R. (2016). On the appropriateness of complex-valued neural networks for speech enhancement. In INTERSPEECH 2016, San Francisco, USA.

Glarner, T., Mahdi Momenzadeh, M., Drude, L., &; Haeb-Umbach, R. (2016). Factor Graph Decoding for Speech Presence Probability Estimation. In 12. ITG Fachtagung Sprachkommunikation (ITG 2016).

Heymann, J., Drude, L., &; Haeb-Umbach, R. (2016). Neural Network Based Spectral Mask Estimation for Acoustic Beamforming. In Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP).

Jacob, F., &; Haeb-Umbach, R. (2016). On the Bias of Direction of Arrival Estimation Using Linear Microphone Arrays. In 12. ITG Fachtagung Sprachkommunikation (ITG 2016).

Heymann, J., Drude, L., &; Haeb-Umbach, R. (2016). Wide Residual BLSTM Network with Discriminative Speaker Adaptation for Robust Speech Recognition. In Computer Speech and Language.

Kinoshita, K., Delcroix, M., Gannot, S., Habets, E. A. P., Haeb-Umbach, R., Kellermann, W.,  Yoshioka, T. (2016). 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.

Plinge, A., Jacob, F., Haeb-Umbach, R., &; Fink, G. A. (2016). Acoustic Microphone Geometry Calibration: An overview and experimental evaluation of state-of-the-art algorithms. IEEE Signal Processing Magazine, 33(4), 14–29.https://doi.org/10.1109/MSP.2016.2555198 

Menne, T., Heymann, J., Alexandridis, A., Irie, K., Zeyer, A., Kitza, M.,  Mouchtaris, A. (2016). The RWTH/UPB/FORTH System Combination for the 4th CHiME Challenge Evaluation. In Computer Speech and Language.

Walter, O., &; Haeb-Umbach, R. (2016). Unsupervised Word Discovery from Speech using Bayesian Hierarchical Models. In 38th German Conference on Pattern Recognition (GCPR 2016).

Schmalenstroeer, J., &; Haeb-Umbach, R. (2016). Investigations into Bluetooth Low Energy Localization Precision Limits. 24th European Signal Processing Conference (EUSIPCO 2016).

Chinaev, A., &; Haeb-Umbach, R. (2015). On Optimal Smoothing in Minimum Statistics Based Noise Tracking. In Interspeech 2015 (pp. 1785–1789).

Despotovic, V., Walter, O., &; Haeb-Umbach, R. (2015). Semantic Analysis of Spoken Input using Markov Logic Networks. In INTERSPEECH 2015.

Drude, L., Jacob, F., &; Haeb-Umbach, R. (2015). DOA-Estimation based on a Complex Watson Kernel Method. In 23th European Signal Processing Conference (EUSIPCO 2015).

Heymann, J., Drude, L., Chinaev, A., &; Haeb-Umbach, R. (2015). BLSTM supported GEV Beamformer Front-End for the 3RD CHiME Challenge. In Automatic Speech Recognition and Understanding Workshop (ASRU 2015).

Heymann, J., Haeb-Umbach, R., Golik, P., &; Schlueter, R. (2015). 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 (pp. 5053–5057).https://doi.org/10.1109/ICASSP.2015.7178933 

Jacob, F., &; Haeb-Umbach, R. (2015). Absolute Geometry Calibration of Distributed Microphone Arrays in an Audio-Visual Sensor Network. ArXiv E-Prints.

Li, J., Deng, L., Haeb-Umbach, R., &; Gong, Y. (2015). Robust Automatic Speech Recognition. Elsevier.

Marchi, E., Schuller, B., Baron-Cohen, S., Golan, O., Boelte, S., Arora, P., &; Haeb-Umbach, R. (2015). Typicality and Emotion in the Voice of Children with Autism Spectrum Condition: Evidence Across Three Languages. In INTERSPEECH 2015.

Walter, O., Drude, L., &; Haeb-Umbach, R. (2015). 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).

Walter, O., Haeb-Umbach, R., Mokbel, B., Paassen, B., &; Hammer, B. (2015). Autonomous Learning of Representations. KI - Kuenstliche Intelligenz, 1–13.http://dx.doi.org/10.1007/s13218-015-0372-1 

Walter, O., Haeb-Umbach, R., Strunk, J., &; P. Himmelmann, N. (2015). Lexicon Discovery for Language Preservation using Unsupervised Word Segmentation with Pitman-Yor Language Models (FGNT-2015-01).

Hoang, M. K., Schmalenstroeer, J., &; Haeb-Umbach, R. (2015). Aligning training models with smartphone properties in WiFi fingerprinting based indoor localization. 40th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2015).

Chinaev, A., Puels, M., &; Haeb-Umbach, R. (2014). Spectral Noise Tracking for Improved Nonstationary Noise Robust ASR. In 11. ITG Fachtagung Sprachkommunikation (ITG 2014).

Drude, L., Chinaev, A., Tran Vu, D. H., &; Haeb-Umbach, R. (2014). 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).

Drude, L., Chinaev, A., Tran Vu, D. H., &; Haeb-Umbach, R. (2014). 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) (pp. 213–217).

Heymann, J., Walter, O., Haeb-Umbach, R., &; Raj, B. (2014). Iterative Bayesian Word Segmentation for Unspuervised Vocabulary Discovery from Phoneme Lattices. In 39th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014).

Jacob, F., &; Haeb-Umbach, R. (2014). 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).

Leutnant, V., Krueger, A., &; Haeb-Umbach, R. (2014). 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, 22(1), 95–109.https://doi.org/10.1109/TASLP.2013.2285480 

Li, J., Deng, L., Gong, Y., &; Haeb-Umbach, R. (2014). An Overview of Noise-Robust Automatic Speech Recognition. IEEE Transactions on Audio, Speech and Language Processing, 22(4), 745–777.https://doi.org/10.1109/TASLP.2014.2304637 

Walter, O., Despotovic, V., Haeb-Umbach, R., Gemmeke, J., Ons, B., &; Van hamme, H. (2014). An Evaluation of Unsupervised Acoustic Model Training for a Dysarthric Speech Interface. In INTERSPEECH 2014.

Schmalenstroeer, J., Jebramcik, P., &; Haeb-Umbach, R. (2014). A combined hardware-software approach for acoustic sensor network synchronization . Signal Processing, 0.http://dx.doi.org/10.1016/j.sigpro.2014.06.030 

Schmalenstroeer, J., Jebramcik, P., &; Haeb-Umbach, R. (2014). A Gossiping Approach to Sampling Clock Synchronization in Wireless Acoustic Sensor Networks. 39th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014).

Schmalenstroeer, J., Zhao, W., &; Haeb-Umbach, R. (2014). Online Observation Error Model Estimation for Acoustic Sensor Network Synchronization. 11. ITG Fachtagung Sprachkommunikation (ITG 2014).

Abdelaziz, A. H., Zeiler, S., Kolossa, D., Leutnant, V., &; Haeb-Umbach, R. (2013). GMM-based significance decoding. In Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on (pp. 6827–6831).https://doi.org/10.1109/ICASSP.2013.6638984 

Chinaev, A., &; Haeb-Umbach, R. (2013). 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) (pp. 3352–3356).https://doi.org/10.1109/ICASSP.2013.6638279 

Chinaev, A., Haeb-Umbach, R., Taghia, J., &; Martin, R. (2013). Improved Single-Channel Nonstationary Noise Tracking by an Optimized MAP-based Postprocessor. In 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013) (pp. 7477–7481).https://doi.org/10.1109/ICASSP.2013.6639116 

Enzner, G., Schmid, D., &; Haeb-Umbach, R. (2013). On the Acoustic Channel Identification in Multi-Microphone Systems via Adaptive Blind Signal Enhancement Techniques. In 21th European Signal Processing Conference (EUSIPCO 2013).

Heymann, J., Walter, O., Haeb-Umbach, R., &; Raj, B. (2013). Unsupervised Word Segmentation from Noisy Input. In Automatic Speech Recognition and Understanding Workshop (ASRU 2013).

Hoang, M. K., &; Haeb-Umbach, R. (2013). 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) (pp. 3721–3725).https://doi.org/10.1109/ICASSP.2013.6638353 

Kinoshita, K., Delcroix, M., Yoshioka, T., Nakatani, T., Habets, E., Haeb-Umbach, R.,  Raj, B. (2013). 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  (pp. 22–23).