Boeddeker, C., Subramanian, A. S., Wichern, G., Haeb-Umbach, R., &; Le Roux, J. (2024). TS-SEP: Joint Diarization and Separation Conditioned on Estimated Speaker Embeddings. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 32, 1185–1197.https://doi.org/10.1109/taslp.2024.3350887 

Cord-Landwehr, T., Boeddeker, C., Zoril, C., Doddipatla, R., &; Haeb-Umbach, R. (2024). Geodesic Interpolation of Frame-Wise Speaker Embeddings for the Diarization of Meeting Scenarios. ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Seoul.https://doi.org/10.1109/icassp48485.2024.10445911 

Gburrek, T., Schmalenstroeer, J., &; Haeb-Umbach, R. (2023). On the Integration of Sampling Rate Synchronization and Acoustic Beamforming. European Signal Processing Conference (EUSIPCO). European Signal Processing Conference (EUSIPCO), Helsinki.

Cord-Landwehr, T., Boeddeker, C., Zoril, C., Doddipatla, R., &; Haeb-Umbach, R. (2023). Frame-Wise and Overlap-Robust Speaker Embeddings for Meeting Diarization. ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Rhodes.https://doi.org/10.1109/icassp49357.2023.10095370 

Schmalenstroeer, J., Gburrek, T., &; Haeb-Umbach, R. (2023). LibriWASN: A Data Set for Meeting Separation, Diarization, and Recognition with Asynchronous Recording Devices. ITG Conference on Speech Communication. ITG Conference on Speech Communication, Aachen.

Cord-Landwehr, T., Boeddeker, C., Zoril, C., Doddipatla, R., &; Haeb-Umbach, R. (2023). A Teacher-Student Approach for Extracting Informative Speaker Embeddings From Speech Mixtures. INTERSPEECH 2023.https://doi.org/10.21437/interspeech.2023-1379 

Rautenberg, F., Kuhlmann, M., Wiechmann, J., Seebauer, F., Wagner, P., &; Haeb-Umbach, R. (2023). On Feature Importance and Interpretability of Speaker Representations. ITG Conference on Speech Communication. ITG Conference on Speech Communication, Aachen.

Wiechmann, J., Rautenberg, F., Wagner, P., &; Haeb-Umbach, R. (2023). Explaining voice characteristics to novice voice practitioners-How successful is it? 20th International Congress of the Phonetic Sciences (ICPhS) .

Berger, S., Vieting, P., Boeddeker, C., Schlüter, R., &; Haeb-Umbach, R. (2023). Mixture Encoder for Joint Speech Separation and Recognition. INTERSPEECH 2023.https://doi.org/10.21437/interspeech.2023-1815 

Seebauer, F., Kuhlmann, M., Haeb-Umbach, R., &; Wagner, P. (2023). Re-examining the quality dimensions of synthetic speech. 12th Speech Synthesis Workshop (SSW) 2023.

von Neumann, T., Kinoshita, K., Boeddeker, C., Delcroix, M., &; Haeb-Umbach, R. (2023). Segment-Less Continuous Speech Separation of Meetings: Training and Evaluation Criteria. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 31, 576–589.https://doi.org/10.1109/taslp.2022.3228629 

von Neumann, T., Boeddeker, C., Kinoshita, K., Delcroix, M., &; Haeb-Umbach, R. (2023). On Word Error Rate Definitions and Their Efficient Computation for Multi-Speaker Speech Recognition Systems. ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).https://doi.org/10.1109/icassp49357.2023.10094784 

von Neumann, T., Boeddeker, C., Delcroix, M., &; Haeb-Umbach, R. (2023). MeetEval: A Toolkit for Computation of Word Error Rates for Meeting Transcription Systems. Proc. CHiME 2023 Workshop on Speech Processing in Everyday Environments. CHiME 2023 Workshop on Speech Processing in Everyday Environments, Dublin.

Gburrek, T., Schmalenstroeer, J., &; Haeb-Umbach, R. (2023). Spatial Diarization for Meeting Transcription with Ad-Hoc Acoustic Sensor Networks. Proc. Asilomar Conference on Signals, Systems, and Computers. 57th Asilomar Conference on Signals, Systems, and Computers.

Rautenberg, F., Kuhlmann, M., Ebbers, J., Wiechmann, J., Seebauer, F., Wagner, P., &; Haeb-Umbach, R. (2023). Speech Disentanglement for Analysis and Modification of Acoustic and Perceptual Speaker Characteristics. Fortschritte Der Akustik - DAGA 2023, 1409–1412.

Boeddeker, C., Cord-Landwehr, T., von Neumann, T., &; Haeb-Umbach, R. (2022). An Initialization Scheme for Meeting Separation with Spatial Mixture Models. Interspeech 2022.https://doi.org/10.21437/interspeech.2022-10929 

Heitkämper, J., Schmalenstroeer, J., &; Haeb-Umbach, R. (n.d.). Neural Network Based Carrier Frequency Offset Estimation From Speech Transmitted Over High Frequency Channels. Proceedings of the 30th European Signal Processing Conference (EUSIPCO). 30th European Signal Processing Conference (EUSIPCO), Belgrad.

Kinoshita, K., von Neumann, T., Delcroix, M., Boeddeker, C., &; Haeb-Umbach, R. (2022). Utterance-by-utterance overlap-aware neural diarization with Graph-PIT. Proc. Interspeech 2022, 1486–1490.https://doi.org/10.21437/Interspeech.2022-11408 

von Neumann, T., Kinoshita, K., Boeddeker, C., Delcroix, M., &; Haeb-Umbach, R. (2022). SA-SDR: A Novel Loss Function for Separation of Meeting Style Data. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).https://doi.org/10.1109/icassp43922.2022.9746757 

Cord-Landwehr, T., von Neumann, T., Boeddeker, C., &; Haeb-Umbach, R. (2022). MMS-MSG: A Multi-purpose Multi-Speaker Mixture Signal Generator. 2022 International Workshop on Acoustic Signal Enhancement (IWAENC). 2022 International Workshop on Acoustic Signal Enhancement (IWAENC), Bamberg.

Cord-Landwehr, T., Boeddeker, C., von Neumann, T., Zorila, C., Doddipatla, R., &; Haeb-Umbach, R. (2022). Monaural source separation: From anechoic to reverberant environments. 2022 International Workshop on Acoustic Signal Enhancement (IWAENC). 2022 International Workshop on Acoustic Signal Enhancement (IWAENC).

Gburrek, T., Schmalenstroeer, J., &; Haeb-Umbach, R. (2022). On Synchronization of Wireless Acoustic Sensor Networks in the Presence of Time-Varying Sampling Rate Offsets and Speaker Changes. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).https://doi.org/10.1109/icassp43922.2022.9746284 

Grimm, C., Fei, T., Warsitz, E., Farhoud, R., Breddermann, T., &; Haeb-Umbach, R. (2022). Warping of Radar Data Into Camera Image for Cross-Modal Supervision in Automotive Applications. IEEE Transactions on Vehicular Technology, 71(9), 9435–9449.https://doi.org/10.1109/TVT.2022.3182411 

Wiechmann, J., Glarner, T., Rautenberg, F., Wagner, P., &; Haeb-Umbach, R. (2022). Technically enabled explaining of voice characteristics. 18. Phonetik Und Phonologie Im Deutschsprachigen Raum (P&;P).

Kuhlmann, M., Seebauer, F., Ebbers, J., Wagner, P., &; Haeb-Umbach, R. (2022). Investigation into Target Speaking Rate Adaptation for Voice Conversion. Interspeech 2022.https://doi.org/10.21437/interspeech.2022-10740 

Gburrek, T., Schmalenstroeer, J., Heitkaemper, J., &; Haeb-Umbach, R. (2022). Informed vs. Blind Beamforming in Ad-Hoc Acoustic Sensor Networks for Meeting Transcription. 2022 International Workshop on Acoustic Signal Enhancement (IWAENC). 17th International Workshop on Acoustic Signal Enhancement (IWAENC 2022),https://doi.org/10.1109/IWAENC53105.2022.9914772__Bamberg, Germany .https://doi.org/10.1109/IWAENC53105.2022.9914772 

Gburrek, T., Boeddeker, C., von Neumann, T., Cord-Landwehr, T., Schmalenstroeer, J., &; Haeb-Umbach, R. (2022). A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network. arXiv.https://doi.org/10.48550/ARXIV.2205.00944 

Ebbers, J., Haeb-Umbach, R., &; Serizel, R. (2022). Threshold Independent Evaluation of Sound Event Detection Scores. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Haeb-Umbach, R., Heymann, J., Drude, L., Watanabe, S., Delcroix, M., &; Nakatani, T. (2021). Far-Field Automatic Speech Recognition. Proceedings of the IEEE, 109(2), 124–148.https://doi.org/10.1109/JPROC.2020.3018668 

Zhang, W., Boeddeker, C., Watanabe, S., Nakatani, T., Delcroix, M., Kinoshita, K., Ochiai, T., Kamo, N., Haeb-Umbach, R., &; Qian, Y. (2021). End-to-End Dereverberation, Beamforming, and Speech Recognition with Improved Numerical Stability and Advanced Frontend. ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).https://doi.org/10.1109/icassp39728.2021.9414464 

Heitkaemper, J., Schmalenstroeer, J., Ion, V., &; Haeb-Umbach, R. (2021). A Database for Research on Detection and Enhancement of Speech Transmitted over HF links. Speech Communication; 14th ITG-Symposium, 1–5.

Boeddeker, C., Rautenberg, F., &; Haeb-Umbach, R. (2021). A Comparison and Combination of Unsupervised Blind Source Separation  Techniques. ITG Conference on Speech Communication. ITG Conference on Speech Communication, Kiel.

Boeddeker, C., Zhang, W., Nakatani, T., Kinoshita, K., Ochiai, T., Delcroix, M., Kamo, N., Qian, Y., &; Haeb-Umbach, R. (2021). Convolutive Transfer Function Invariant SDR Training Criteria for Multi-Channel Reverberant Speech Separation. ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).https://doi.org/10.1109/icassp39728.2021.9414661 

Schmalenstroeer, J., Heitkaemper, J., Ullmann, J., &; Haeb-Umbach, R. (2021). Open Range Pitch Tracking for Carrier Frequency Difference Estimation from HF Transmitted Speech. 29th European Signal Processing Conference (EUSIPCO), 1–5.

Gburrek, T., Schmalenstroeer, J., &; Haeb-Umbach, R. (2021). Geometry calibration in wireless acoustic sensor networks utilizing DoA and distance information. EURASIP Journal on Audio, Speech, and Music Processing.https://doi.org/10.1186/s13636-021-00210-x 

Gburrek, T., Schmalenstroeer, J., &; Haeb-Umbach, R. (2021). Iterative Geometry Calibration from Distance Estimates for Wireless Acoustic Sensor Networks. ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).https://doi.org/10.1109/icassp39728.2021.9413831 

Gburrek, T., Schmalenstroeer, J., &; Haeb-Umbach, R. (2021). On Source-Microphone Distance Estimation Using Convolutional Recurrent Neural Networks. Speech Communication; 14th ITG-Symposium, 1–5.

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

von Neumann, T., Kinoshita, K., Boeddeker, C., Delcroix, M., &; Haeb-Umbach, R. (2021). Graph-PIT: Generalized Permutation Invariant Training for Continuous Separation of Arbitrary Numbers of Speakers. Interspeech 2021. Interspeech.https://doi.org/10.21437/interspeech.2021-1177 

von Neumann, T., Boeddeker, C., Kinoshita, K., Delcroix, M., &; Haeb-Umbach, R. (2021). Speeding Up Permutation Invariant Training for Source Separation. Speech Communication; 14th ITG Conference. Speech Communication; 14th ITG Conference, Kiel.

Ebbers, J., &; Haeb-Umbach, R. (2021). Self-Trained Audio Tagging and Sound Event Detection in Domestic Environments. Proceedings of the 6th Detection and Classification of Acoustic Scenes and Events 2021 Workshop (DCA), 226–230.

Ebbers, J., Keyser, M. C., &; Haeb-Umbach, R. (2021). Adapting Sound Recognition to A New Environment Via Self-Training. Proceedings of the 29th European Signal Processing Conference (EUSIPCO), 1135–1139.

Rohlfing, K. J., Cimiano, P., Scharlau, I., Matzner, T., Buhl, H. M., Buschmeier, H., Esposito, E., Grimminger, A., Hammer, B., Haeb-Umbach, R., Horwath, I., Hüllermeier, E., Kern, F., Kopp, S., Thommes, K., Ngonga Ngomo, A.-C., Schulte, C., Wachsmuth, H., Wagner, P., &; Wrede, B. (2021). Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems. IEEE Transactions on Cognitive and Developmental Systems, 13(3), 717–728.https://doi.org/10.1109/tcds.2020.3044366 

Haeb-Umbach, R. (2020). Sprachtechnologien für Digitale Assistenten. In R. Böck, I. Siegert, &; A. Wendemuth (Eds.), Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2020 (pp. 227–234). TUDpress, Dresden.

Boeddeker, C., Cord-Landwehr, T., Heitkaemper, J., Zorila, C., Hayakawa, D., Li, M.,  Haeb-Umbach, R. (2020). Towards a speaker diarization system for the CHiME 2020 dinner party transcription. In Proc. CHiME 2020 Workshop on Speech Processing in Everyday Environments.

Nakatani, T., Boeddeker, C., Kinoshita, K., Ikeshita, R., Delcroix, M., &; Haeb-Umbach, R. (2020). Jointly optimal denoising, dereverberation, and source separation. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 1–1.https://doi.org/10.1109/TASLP.2020.3013118 

Heitkaemper, J., Jakobeit, D., Boeddeker, C., Drude, L., &; Haeb-Umbach, R. (2020). Demystifying TasNet: A Dissecting Approach. ICASSP 2020 Virtual Barcelona Spain.

Heitkaemper, J., Schmalenstroeer, J., &; Haeb-Umbach, R. (2020). Statistical and Neural Network Based Speech Activity Detection in Non-Stationary Acoustic Environments. INTERSPEECH 2020 Virtual Shanghai China.

von Neumann, T., Kinoshita, K., Drude, L., Boeddeker, C., Delcroix, M., Nakatani, T., &; Haeb-Umbach, R. (2020). End-to-End Training of Time Domain Audio Separation and Recognition. ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 7004–7008.https://doi.org/10.1109/ICASSP40776.2020.9053461 

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 

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.

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.

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.

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).