Publikationen
On the Integration of Sampling Rate Synchronization and Acoustic Beamforming
T. Gburrek, J. Schmalenstroeer, R. Haeb-Umbach, in: European Signal Processing Conference (EUSIPCO), 2023.
Frame-Wise and Overlap-Robust Speaker Embeddings for Meeting Diarization
T. Cord-Landwehr, C. Boeddeker, C. Zorilă, R. Doddipatla, R. Haeb-Umbach, in: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, 2023.
LibriWASN: A Data Set for Meeting Separation, Diarization, and Recognition with Asynchronous Recording Devices
J. Schmalenstroeer, T. Gburrek, R. Haeb-Umbach, in: ITG Conference on Speech Communication, 2023.
A Teacher-Student Approach for Extracting Informative Speaker Embeddings From Speech Mixtures
T. Cord-Landwehr, C. Boeddeker, C. Zorilă, R. Doddipatla, R. Haeb-Umbach, in: INTERSPEECH 2023, ISCA, 2023.
On Feature Importance and Interpretability of Speaker Representations
F. Rautenberg, M. Kuhlmann, J. Wiechmann, F. Seebauer, P. Wagner, R. Haeb-Umbach, in: ITG Conference on Speech Communication, 2023.
Explaining voice characteristics to novice voice practitioners-How successful is it?
J. Wiechmann, F. Rautenberg, P. Wagner, R. Haeb-Umbach, in: 20th International Congress of the Phonetic Sciences (ICPhS) , 2023.
Reverberation as Supervision For Speech Separation
R. Aralikatti, C. Boeddeker, G. Wichern, A. Subramanian, J. Le Roux, in: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, 2023.
Mixture Encoder for Joint Speech Separation and Recognition
S. Berger, P. Vieting, C. Boeddeker, R. Schlüter, R. Haeb-Umbach, in: INTERSPEECH 2023, ISCA, 2023.
Re-examining the quality dimensions of synthetic speech
F. Seebauer, M. Kuhlmann, R. Haeb-Umbach, P. Wagner, in: 12th Speech Synthesis Workshop (SSW) 2023, 2023.
Segment-Less Continuous Speech Separation of Meetings: Training and Evaluation Criteria
T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, R. Haeb-Umbach, IEEE/ACM Transactions on Audio, Speech, and Language Processing 31 (2023) 576–589.
On Word Error Rate Definitions and Their Efficient Computation for Multi-Speaker Speech Recognition Systems
T. von Neumann, C. Boeddeker, K. Kinoshita, M. Delcroix, R. Haeb-Umbach, in: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, 2023.
MeetEval: A Toolkit for Computation of Word Error Rates for Meeting Transcription Systems
T. von Neumann, C. Boeddeker, M. Delcroix, R. Haeb-Umbach, in: Proc. CHiME 2023 Workshop on Speech Processing in Everyday Environments, 2023.
Spatial Diarization for Meeting Transcription with Ad-Hoc Acoustic Sensor Networks
T. Gburrek, J. Schmalenstroeer, R. Haeb-Umbach, in: Proc. Asilomar Conference on Signals, Systems, and Computers, 2023.
Post-Processing Independent Evaluation of Sound Event Detection Systems
J. Ebbers, R. Haeb-Umbach, R. Serizel, in: Proceedings of the 8th Detection and Classification of Acoustic Scenes and Events 2023 Workshop (DCASE2023), Tampere, Finland, 2023, pp. 36–40.
Speech Disentanglement for Analysis and Modification of Acoustic and Perceptual Speaker Characteristics
F. Rautenberg, M. Kuhlmann, J. Ebbers, J. Wiechmann, F. Seebauer, P. Wagner, R. Haeb-Umbach, in: Fortschritte Der Akustik - DAGA 2023, 2023, pp. 1409–1412.
End-to-End Dereverberation, Beamforming, and Speech Recognition in A Cocktail Party
W. Zhang, X. Chang, C. Boeddeker, T. Nakatani, S. Watanabe, Y. Qian, IEEE/ACM Transactions on Audio, Speech, and Language Processing (2022).
An Initialization Scheme for Meeting Separation with Spatial Mixture Models
C. Boeddeker, T. Cord-Landwehr, T. von Neumann, R. Haeb-Umbach, in: Interspeech 2022, ISCA, 2022.
Neural Network Based Carrier Frequency Offset Estimation From Speech Transmitted Over High Frequency Channels
J. Heitkämper, J. Schmalenstroeer, R. Haeb-Umbach, in: Proceedings of the 30th European Signal Processing Conference (EUSIPCO), Belgrad, n.d.
Data-driven Time Synchronization in Wireless Multimedia Networks
H. Afifi, H. Karl, T. Gburrek, J. Schmalenstroeer, in: 2022 International Wireless Communications and Mobile Computing (IWCMC), IEEE, 2022.
Utterance-by-utterance overlap-aware neural diarization with Graph-PIT
K. Kinoshita, T. von Neumann, M. Delcroix, C. Boeddeker, R. Haeb-Umbach, in: Proc. Interspeech 2022, ISCA, 2022, pp. 1486–1490.
SA-SDR: A Novel Loss Function for Separation of Meeting Style Data
T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, R. Haeb-Umbach, in: ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, 2022.
MMS-MSG: A Multi-purpose Multi-Speaker Mixture Signal Generator
T. Cord-Landwehr, T. von Neumann, C. Boeddeker, R. Haeb-Umbach, in: 2022 International Workshop on Acoustic Signal Enhancement (IWAENC), 2022.
Monaural source separation: From anechoic to reverberant environments
T. Cord-Landwehr, C. Boeddeker, T. von Neumann, C. Zorila, R. Doddipatla, R. Haeb-Umbach, in: 2022 International Workshop on Acoustic Signal Enhancement (IWAENC), IEEE, Bamberg, 2022.
On Synchronization of Wireless Acoustic Sensor Networks in the Presence of Time-Varying Sampling Rate Offsets and Speaker Changes
T. Gburrek, J. Schmalenstroeer, R. Haeb-Umbach, in: ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, 2022.
Warping of Radar Data Into Camera Image for Cross-Modal Supervision in Automotive Applications
C. Grimm, T. Fei, E. Warsitz, R. Farhoud, T. Breddermann, R. Haeb-Umbach, IEEE Transactions on Vehicular Technology 71 (2022) 9435–9449.
Pre-Training And Self-Training For Sound Event Detection In Domestic Environments
J. Ebbers, R. Haeb-Umbach, Pre-Training And Self-Training For Sound Event Detection In Domestic Environments, 2022.
Technically enabled explaining of voice characteristics
J. Wiechmann, T. Glarner, F. Rautenberg, P. Wagner, R. Haeb-Umbach, in: 18. Phonetik Und Phonologie Im Deutschsprachigen Raum (P&P), 2022.
Investigation into Target Speaking Rate Adaptation for Voice Conversion
M. Kuhlmann, F. Seebauer, J. Ebbers, P. Wagner, R. Haeb-Umbach, in: Interspeech 2022, ISCA, 2022.
Informed vs. Blind Beamforming in Ad-Hoc Acoustic Sensor Networks for Meeting Transcription
T. Gburrek, J. Schmalenstroeer, J. Heitkaemper, R. Haeb-Umbach, in: 2022 International Workshop on Acoustic Signal Enhancement (IWAENC), IEEE, 2022.
A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network
T. Gburrek, C. Boeddeker, T. von Neumann, T. Cord-Landwehr, J. Schmalenstroeer, R. Haeb-Umbach, A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network, arXiv, 2022.
Threshold Independent Evaluation of Sound Event Detection Scores
J. Ebbers, R. Haeb-Umbach, R. Serizel, in: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022.
Far-Field Automatic Speech Recognition
R. Haeb-Umbach, J. Heymann, L. Drude, S. Watanabe, M. Delcroix, T. Nakatani, Proceedings of the IEEE 109 (2021) 124–148.
End-to-End Dereverberation, Beamforming, and Speech Recognition with Improved Numerical Stability and Advanced Frontend
W. Zhang, C. Boeddeker, S. Watanabe, T. Nakatani, M. Delcroix, K. Kinoshita, T. Ochiai, N. Kamo, R. Haeb-Umbach, Y. Qian, in: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021.
ESPnet-SE: End-To-End Speech Enhancement and Separation Toolkit Designed for ASR Integration
C. Li, J. Shi, W. Zhang, A.S. Subramanian, X. Chang, N. Kamo, M. Hira, T. Hayashi, C. Boeddeker, Z. Chen, S. Watanabe, in: 2021 IEEE Spoken Language Technology Workshop (SLT), 2021.
Dual-Path RNN for Long Recording Speech Separation
C. Li, Y. Luo, C. Han, J. Li, T. Yoshioka, T. Zhou, M. Delcroix, K. Kinoshita, C. Boeddeker, Y. Qian, S. Watanabe, Z. Chen, in: 2021 IEEE Spoken Language Technology Workshop (SLT), 2021.
A Database for Research on Detection and Enhancement of Speech Transmitted over HF links
J. Heitkaemper, J. Schmalenstroeer, V. Ion, R. Haeb-Umbach, in: Speech Communication; 14th ITG-Symposium, 2021, pp. 1–5.
A Comparison and Combination of Unsupervised Blind Source Separation Techniques
C. Boeddeker, F. Rautenberg, R. Haeb-Umbach, in: ITG Conference on Speech Communication, 2021.
Convolutive Transfer Function Invariant SDR Training Criteria for Multi-Channel Reverberant Speech Separation
C. Boeddeker, W. Zhang, T. Nakatani, K. Kinoshita, T. Ochiai, M. Delcroix, N. Kamo, Y. Qian, R. Haeb-Umbach, in: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021.
Open Range Pitch Tracking for Carrier Frequency Difference Estimation from HF Transmitted Speech
J. Schmalenstroeer, J. Heitkaemper, J. Ullmann, R. Haeb-Umbach, in: 29th European Signal Processing Conference (EUSIPCO), 2021, pp. 1–5.
Geometry calibration in wireless acoustic sensor networks utilizing DoA and distance information
T. Gburrek, J. Schmalenstroeer, R. Haeb-Umbach, EURASIP Journal on Audio, Speech, and Music Processing (2021).
Iterative Geometry Calibration from Distance Estimates for Wireless Acoustic Sensor Networks
T. Gburrek, J. Schmalenstroeer, R. Haeb-Umbach, in: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021.
On Source-Microphone Distance Estimation Using Convolutional Recurrent Neural Networks
T. Gburrek, J. Schmalenstroeer, R. Haeb-Umbach, in: Speech Communication; 14th ITG-Symposium, 2021, pp. 1–5.
Online Estimation of Sampling Rate Offsets in Wireless Acoustic Sensor Networks with Packet Loss
A. Chinaev, G. Enzner, T. Gburrek, J. Schmalenstroeer, in: 29th European Signal Processing Conference (EUSIPCO), 2021, pp. 1–5.
Contrastive Predictive Coding Supported Factorized Variational Autoencoder for Unsupervised Learning of Disentangled Speech Representations
J. Ebbers, M. Kuhlmann, T. Cord-Landwehr, R. Haeb-Umbach, in: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, pp. 3860–3864.
Graph-PIT: Generalized Permutation Invariant Training for Continuous Separation of Arbitrary Numbers of Speakers
T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, R. Haeb-Umbach, in: Interspeech 2021, 2021.
Speeding Up Permutation Invariant Training for Source Separation
T. von Neumann, C. Boeddeker, K. Kinoshita, M. Delcroix, R. Haeb-Umbach, in: Speech Communication; 14th ITG Conference, 2021.
Self-Trained Audio Tagging and Sound Event Detection in Domestic Environments
J. Ebbers, R. Haeb-Umbach, in: Proceedings of the 6th Detection and Classification of Acoustic Scenes and Events 2021 Workshop (DCASE2021), Barcelona, Spain, 2021, pp. 226–230.
Adapting Sound Recognition to A New Environment Via Self-Training
J. Ebbers, M.C. Keyser, R. Haeb-Umbach, in: Proceedings of the 29th European Signal Processing Conference (EUSIPCO), 2021, pp. 1135–1139.
Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems
K.J. Rohlfing, P. Cimiano, I. Scharlau, T. Matzner, H.M. Buhl, H. Buschmeier, E. Esposito, A. Grimminger, B. Hammer, R. Haeb-Umbach, I. Horwath, E. Hüllermeier, F. Kern, S. Kopp, K. Thommes, A.-C. Ngonga Ngomo, C. Schulte, H. Wachsmuth, P. Wagner, B. Wrede, IEEE Transactions on Cognitive and Developmental Systems 13 (2021) 717–728.
Sprachtechnologien für Digitale Assistenten
R. Haeb-Umbach, in: R. Böck, I. Siegert, A. Wendemuth (Eds.), Studientexte Zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2020, TUDpress, Dresden, 2020, pp. 227–234.
Jointly Optimal Dereverberation and Beamforming
C. Boeddeker, T. Nakatani, K. Kinoshita, R. Haeb-Umbach, in: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020.
Towards a speaker diarization system for the CHiME 2020 dinner party transcription
C. Boeddeker, T. Cord-Landwehr, J. Heitkaemper, C. Zorila, D. Hayakawa, M. Li, M. Liu, R. Doddipatla, R. Haeb-Umbach, in: Proc. CHiME 2020 Workshop on Speech Processing in Everyday Environments, 2020.
Jointly optimal denoising, dereverberation, and source separation
T. Nakatani, C. Boeddeker, K. Kinoshita, R. Ikeshita, M. Delcroix, R. Haeb-Umbach, IEEE/ACM Transactions on Audio, Speech, and Language Processing (2020) 1–1.
Demystifying TasNet: A Dissecting Approach
J. Heitkaemper, D. Jakobeit, C. Boeddeker, L. Drude, R. Haeb-Umbach, in: ICASSP 2020 Virtual Barcelona Spain, 2020.
CHiME-6 Challenge:Tackling Multispeaker Speech Recognition for Unsegmented Recordings
S. Watanabe, M. Mandel, J. Barker, E. Vincent, A. Arora, X. Chang, S. Khudanpur, V. Manohar, D. Povey, D. Raj, D. Snyder, A.S. Subramanian, J. Trmal, B.B. Yair, C. Boeddeker, Z. Ni, Y. Fujita, S. Horiguchi, N. Kanda, T. Yoshioka, N. Ryant, ArXiv:2004.09249 (2020).
Statistical and Neural Network Based Speech Activity Detection in Non-Stationary Acoustic Environments
J. Heitkaemper, J. Schmalenstroeer, R. Haeb-Umbach, in: INTERSPEECH 2020 Virtual Shanghai China, 2020.
End-to-End Training of Time Domain Audio Separation and Recognition
T. von Neumann, K. Kinoshita, L. Drude, C. Boeddeker, M. Delcroix, T. Nakatani, R. Haeb-Umbach, in: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, pp. 7004–7008.
Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source Counting, Separation and ASR
T. von Neumann, C. Boeddeker, L. Drude, K. Kinoshita, M. Delcroix, T. Nakatani, R. Haeb-Umbach, in: Proc. Interspeech 2020, 2020, pp. 3097–3101.
Deep Neural Network based Distance Estimation for Geometry Calibration in Acoustic Sensor Network
T. Gburrek, J. Schmalenstroeer, A. Brendel, W. Kellermann, R. Haeb-Umbach, in: European Signal Processing Conference (EUSIPCO), 2020.
Multi-Path RNN for Hierarchical Modeling of Long Sequential Data and its Application to Speaker Stream Separation
K. Kinoshita, T. von Neumann, M. Delcroix, T. Nakatani, R. Haeb-Umbach, in: Proc. Interspeech 2020, 2020, pp. 2652–2656.
Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-Supervised Sound Event Detection
J. Ebbers, R. Haeb-Umbach, in: Proceedings of the Detection and Classification of Acoustic Scenes and Events 2020 Workshop (DCASE2020), 2020.
SMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition
L. Drude, J. Heitkaemper, C. Boeddeker, R. Haeb-Umbach, ArXiv E-Prints (2019).
Unsupervised training of neural mask-based beamforming
L. Drude, J. Heymann, R. Haeb-Umbach, in: INTERSPEECH 2019, Graz, Austria, 2019.
Unsupervised Training of a Deep Clustering Model for Multichannel Blind Source Separation
L. Drude, D. Hasenklever, R. Haeb-Umbach, in: ICASSP 2019, Brighton, UK, 2019.
Joint Optimization of Neural Network-based WPE Dereverberation and Acoustic Model for Robust Online ASR
J. Heymann, L. Drude, R. Haeb-Umbach, K. Kinoshita, T. Nakatani, in: ICASSP 2019, Brighton, UK, 2019.
Directional Statistics and Filtering Using libDirectional
G. Kurz, I. Gilitschenski, F. Pfaff, L. Drude, U.D. Hanebeck, R. Haeb-Umbach, R.Y. Siegwart, in: Journal of Statistical Software 89(4), 2019.
Integration of Neural Networks and Probabilistic Spatial Models for Acoustic Blind Source Separation
L. Drude, R. Haeb-Umbach, IEEE Journal of Selected Topics in Signal Processing (2019).
Improving CTC Using Stimulated Learning for Sequence Modeling
J. Heymann, B.L. Khe Chai Sim, in: ICASSP 2019, Brighton, UK, 2019.
An Investigation Into the Effectiveness of Enhancement in ASR Training and Test for Chime-5 Dinner Party Transcription
C. Zorila, C. Boeddeker, R. Doddipatla, R. Haeb-Umbach, in: ASRU 2019, Sentosa, Singapore, 2019.
A Study on Online Source Extraction in the Presence of Changing Speaker Positions
J. Heitkaemper, T. Feher, M. Freitag, R. Haeb-Umbach, in: International Conference on Statistical Language and Speech Processing 2019, Ljubljana, Slovenia, 2019.
Multi-Channel Block-Online Source Extraction based on Utterance Adaptation
J.M. Martin-Donas, J. Heitkaemper, R. Haeb-Umbach, A.M. Gomez, A.M. Peinado, in: INTERSPEECH 2019, Graz, Austria, 2019.
Guided Source Separation Meets a Strong ASR Backend: Hitachi/Paderborn University Joint Investigation for Dinner Party ASR
N. Kanda, C. Boeddeker, J. Heitkaemper, Y. Fujita, S. Horiguchi, R. Haeb-Umbach, in: INTERSPEECH 2019, Graz, Austria, 2019.
All-neural Online Source Separation, Counting, and Diarization for Meeting Analysis
T. von Neumann, K. Kinoshita, M. Delcroix, S. Araki, T. Nakatani, R. Haeb-Umbach, in: ICASSP 2019, Brighton, UK, 2019.
Speech Processing for Digital Home Assistance: Combining Signal Processing With Deep-Learning Techniques
R. Haeb-Umbach, S. Watanabe, T. Nakatani, M. Bacchiani, B. Hoffmeister, M.L. Seltzer, H. Zen, M. Souden, IEEE Signal Processing Magazine 36 (2019) 111–124.
Unsupervised Learning of a Disentangled Speech Representation for Voice Conversion
T. Gburrek, T. Glarner, J. Ebbers, R. Haeb-Umbach, P. Wagner, in: Proc. 10th ISCA Speech Synthesis Workshop, 2019, pp. 81–86.
Convolutional Recurrent Neural Network and Data Augmentation for Audio Tagging with Noisy Labels and Minimal Supervision
J. Ebbers, R. Haeb-Umbach, in: DCASE2019 Workshop, New York, USA, 2019.
Weakly Supervised Sound Activity Detection and Event Classification in Acoustic Sensor Networks
J. Ebbers, L. Drude, R. Haeb-Umbach, A. Brendel, W. Kellermann, in: CAMSAP 2019, Guadeloupe, West Indies, 2019.
Privacy-preserving Variational Information Feature Extraction for Domestic Activity Monitoring Versus Speaker Identification
A. Nelus, J. Ebbers, R. Haeb-Umbach, R. Martin, in: INTERSPEECH 2019, Graz, Austria, 2019.
Performance of Mask Based Statistical Beamforming in a Smart Home Scenario
J. Heymann, M. Bacchiani, T.N. Sainath, in: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018, pp. 6722–6726.
Evaluation of Modulation-MFCC Features and DNN Classification for Acoustic Event Detection
J. Ebbers, A. Nelus, R. Martin, R. Haeb-Umbach, in: DAGA 2018, München, 2018.
Frame-Online DNN-WPE Dereverberation
J. Heymann, L. Drude, R. Haeb-Umbach, K. Kinoshita, T. Nakatani, in: IWAENC 2018, Tokio, Japan, 2018.
Smoothing along Frequency in Online Neural Network Supported Acoustic Beamforming
J. Heitkaemper, J. Heymann, R. Haeb-Umbach, in: ITG 2018, Oldenburg, Germany, 2018.
Integration neural network based beamforming and weighted prediction error dereverberation
L. Drude, C. Boeddeker, J. Heymann, K. Kinoshita, M. Delcroix, T. Nakatani, R. Haeb-Umbach, in: INTERSPEECH 2018, Hyderabad, India, 2018.
NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing
L. Drude, J. Heymann, C. Boeddeker, R. Haeb-Umbach, in: ITG 2018, Oldenburg, Germany, 2018.
Machine learning techniques for semantic analysis of dysarthric speech: An experimental study
V. Despotovic, O. Walter, R. Haeb-Umbach, Speech Communication 99 (2018) 242-251 (Elsevier B.V.) (2018).
Deep Attractor Networks for Speaker Re-Identifikation and Blind Source Separation
L. Drude, T. von Neumann, R. Haeb-Umbach, in: ICASSP 2018, Calgary, Canada, 2018.
Dual Frequency- and Block-Permutation Alignment for Deep Learning Based Block-Online Blind Source Separation
L. Drude, Takuya Higuchi, K. Kinoshita, T. Nakatani, R. Haeb-Umbach, in: ICASSP 2018, Calgary, Canada, 2018.
Exploring Practical Aspects of Neural Mask-Based Beamforming for Far-Field Speech Recognition
C. Boeddeker, H. Erdogan, T. Yoshioka, R. Haeb-Umbach, in: ICASSP 2018, Calgary, Canada, 2018.
ESPnet: End-to-End Speech Processing Toolkit
S. Watanabe, T. Hori, S. Karita, T. Hayashi, J. Nishitoba, Y. Unno, N. Enrique Yalta Soplin, J. Heymann, M. Wiesner, N. Chen, A. Renduchintala, T. Ochiai, in: INTERSPEECH 2018, Hyderabad, India, 2018, pp. 2207–2211.
Front-End Processing for the CHiME-5 Dinner Party Scenario
C. Boeddeker, J. Heitkaemper, J. Schmalenstroeer, L. Drude, J. Heymann, R. Haeb-Umbach, in: Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India, 2018.
MARVELO - A Framework for Signal Processing in Wireless Acoustic Sensor Networks
H. Afifi, J. Schmalenstroeer, J. Ullmann, R. Haeb-Umbach, H. Karl, in: Speech Communication; 13th ITG-Symposium, 2018, pp. 1–5.
Discrimination of Stationary from Moving Targets with Recurrent Neural Networks in Automotive Radar
C. Grimm, T. Breddermann, R. Farhoud, T. Fei, E. Warsitz, R. Haeb-Umbach, in: International Conference on Microwaves for Intelligent Mobility (ICMIM) 2018, 2018.
Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery
T. Glarner, P. Hanebrink, J. Ebbers, R. Haeb-Umbach, in: INTERSPEECH 2018, Hyderabad, India, 2018.
Efficient Sampling Rate Offset Compensation - An Overlap-Save Based Approach
J. Schmalenstroeer, R. Haeb-Umbach, in: 26th European Signal Processing Conference (EUSIPCO 2018), 2018.
The RWTH/UPB System Combination for the CHiME 2018 Workshop
M. Kitza, W. Michel, C. Boeddeker, J. Heitkaemper, T. Menne, R. Schlüter, H. Ney, J. Schmalenstroeer, L. Drude, J. Heymann, R. Haeb-Umbach, in: Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India, 2018.
Benchmarking Neural Network Architectures for Acoustic Sensor Networks
J. Ebbers, J. Heitkaemper, J. Schmalenstroeer, R. Haeb-Umbach, in: ITG 2018, Oldenburg, Germany, 2018.
Insights into the Interplay of Sampling Rate Offsets and MVDR Beamforming
J. Schmalenstroeer, R. Haeb-Umbach, in: ITG 2018, Oldenburg, Germany, 2018.
A Study on Transfer Learning for Acoustic Event Detection in a Real Life Scenario
P. Arora, R. Haeb-Umbach, in: IEEE 19th International Workshop on Multimedia Signal Processing (MMSP), 2017.
On the Computation of Complex-valued Gradients with Application to Statistically Optimum Beamforming
C. Boeddeker, P. Hanebrink, L. Drude, J. Heymann, R. Haeb-Umbach, On the Computation of Complex-Valued Gradients with Application to Statistically Optimum Beamforming, 2017.
Optimizing Neural-Network Supported Acoustic Beamforming by Algorithmic Differentiation
C. Boeddeker, P. Hanebrink, L. Drude, J. Heymann, R. Haeb-Umbach, in: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.
A Generalized Log-Spectral Amplitude Estimator for Single-Channel Speech Enhancement
A. Chinaev, R. Haeb-Umbach, in: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.
Tight integration of spatial and spectral features for BSS with Deep Clustering embeddings
L. Drude, R. Haeb-Umbach, in: INTERSPEECH 2017, Stockholm, Schweden, 2017.
Leveraging Text Data for Word Segmentation for Underresourced Languages
T. Glarner, B. Boenninghoff, O. Walter, R. Haeb-Umbach, in: INTERSPEECH 2017, Stockholm, Schweden, 2017.
BEAMNET: End-to-End Training of a Beamformer-Supported Multi-Channel ASR System
J. Heymann, L. Drude, C. Boeddeker, P. Hanebrink, R. Haeb-Umbach, in: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.
A Generic Neural Acoustic Beamforming Architecture for Robust Multi-Channel Speech Processing
J. Heymann, L. Drude, R. Haeb-Umbach, Computer Speech and Language (2017).
Building or Enclosure Termination Closing and/or Opening Apparatus, and Method for Operating a Building or Enclosure Termination
F. Jacob, J. Schmalenstroeer, (2017).
A Novel Target Separation Algorithm Applied to The Two-Dimensional Spectrum for FMCW Automotive Radar Systems
T. Fei, C. Grimm, R. Farhoud, T. Breddermann, E. Warsitz, R. Haeb-Umbach, in: IEEE International Conference on Microwave, Communications, Anthenas and Electronic Systems, 2017.
Hypothesis Test for the Detection of Moving Targets in Automotive Radar
C. Grimm, T. Breddermann, R. Farhoud, T. Fei, E. Warsitz, R. Haeb-Umbach, in: IEEE International Conference on Microwave, Communications, Anthenas and Electronic Systems (COMCAS), 2017.
Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery
J. Ebbers, J. Heymann, L. Drude, T. Glarner, R. Haeb-Umbach, B. Raj, in: INTERSPEECH 2017, Stockholm, Schweden, 2017.
Multi-Stage Coherence Drift Based Sampling Rate Synchronization for Acoustic Beamforming
J. Schmalenstroeer, J. Heymann, L. Drude, C. Boeddeker, R. Haeb-Umbach, in: IEEE 19th International Workshop on Multimedia Signal Processing (MMSP), 2017.
Detection of Moving Targets in Automotive Radar with Distorted Ego-Velocity Information
C. Grimm, R. Farhoud, T. Fei, E. Warsitz, R. Haeb-Umbach, in: IEEE Microwaves, Radar and Remote Sensing Symposium (MRRS), 2017.
A Priori SNR Estimation Using a Generalized Decision Directed Approach
A. Chinaev, R. Haeb-Umbach, in: INTERSPEECH 2016, San Francisco, USA, 2016.
A Priori SNR Estimation Using Weibull Mixture Model
A. Chinaev, J. Heitkaemper, R. Haeb-Umbach, in: 12. ITG Fachtagung Sprachkommunikation (ITG 2016), 2016.
Noise-Presence-Probability-Based Noise PSD Estimation by Using DNNs
A. Chinaev, J. Heymann, L. Drude, R. Haeb-Umbach, in: 12. ITG Fachtagung Sprachkommunikation (ITG 2016), 2016.
Blind Speech Separation based on Complex Spherical k-Mode Clustering
L. Drude, C. Boeddeker, R. Haeb-Umbach, in: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2016.
On the appropriateness of complex-valued neural networks for speech enhancement
L. Drude, B. Raj, R. Haeb-Umbach, in: INTERSPEECH 2016, San Francisco, USA, 2016.
Factor Graph Decoding for Speech Presence Probability Estimation
T. Glarner, M. Mahdi Momenzadeh, L. Drude, R. Haeb-Umbach, in: 12. ITG Fachtagung Sprachkommunikation (ITG 2016), 2016.
Neural Network Based Spectral Mask Estimation for Acoustic Beamforming
J. Heymann, L. Drude, R. Haeb-Umbach, in: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2016.
On the Bias of Direction of Arrival Estimation Using Linear Microphone Arrays
F. Jacob, R. Haeb-Umbach, in: 12. ITG Fachtagung Sprachkommunikation (ITG 2016), 2016.
Wide Residual BLSTM Network with Discriminative Speaker Adaptation for Robust Speech Recognition
J. Heymann, L. Drude, R. Haeb-Umbach, in: Computer Speech and Language, 2016.
A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research
K. Kinoshita, M. Delcroix, S. Gannot, E.A.P. Habets, R. Haeb-Umbach, W. Kellermann, V. Leutnant, R. Maas, T. Nakatani, B. Raj, A. Sehr, T. Yoshioka, EURASIP Journal on Advances in Signal Processing (2016).
Acoustic Microphone Geometry Calibration: An overview and experimental evaluation of state-of-the-art algorithms
A. Plinge, F. Jacob, R. Haeb-Umbach, G.A. Fink, IEEE Signal Processing Magazine 33 (2016) 14–29.
The RWTH/UPB/FORTH System Combination for the 4th CHiME Challenge Evaluation
T. Menne, J. Heymann, A. Alexandridis, K. Irie, A. Zeyer, M. Kitza, P. Golik, I. Kulikov, L. Drude, R. Schlüter, H. Ney, R. Haeb-Umbach, A. Mouchtaris, in: Computer Speech and Language, 2016.
Unsupervised Word Discovery from Speech using Bayesian Hierarchical Models
O. Walter, R. Haeb-Umbach, in: 38th German Conference on Pattern Recognition (GCPR 2016), 2016.
Investigations into Bluetooth Low Energy Localization Precision Limits
J. Schmalenstroeer, R. Haeb-Umbach, in: 24th European Signal Processing Conference (EUSIPCO 2016), 2016.
On Optimal Smoothing in Minimum Statistics Based Noise Tracking
A. Chinaev, R. Haeb-Umbach, in: Interspeech 2015, 2015, pp. 1785–1789.
Semantic Analysis of Spoken Input using Markov Logic Networks
V. Despotovic, O. Walter, R. Haeb-Umbach, in: INTERSPEECH 2015, 2015.
DOA-Estimation based on a Complex Watson Kernel Method
L. Drude, F. Jacob, R. Haeb-Umbach, in: 23th European Signal Processing Conference (EUSIPCO 2015), 2015.
BLSTM supported GEV Beamformer Front-End for the 3RD CHiME Challenge
J. Heymann, L. Drude, A. Chinaev, R. Haeb-Umbach, in: Automatic Speech Recognition and Understanding Workshop (ASRU 2015), 2015.
Unsupervised adaptation of a denoising autoencoder by Bayesian Feature Enhancement for reverberant asr under mismatch conditions
J. Heymann, R. Haeb-Umbach, P. Golik, R. Schlueter, in: Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference On, 2015, pp. 5053–5057.
Absolute Geometry Calibration of Distributed Microphone Arrays in an Audio-Visual Sensor Network
F. Jacob, R. Haeb-Umbach, ArXiv E-Prints (2015).
Robust Automatic Speech Recognition
J. Li, L. Deng, R. Haeb-Umbach, Y. Gong, Robust Automatic Speech Recognition, Elsevier, 2015.
Typicality and Emotion in the Voice of Children with Autism Spectrum Condition: Evidence Across Three Languages
E. Marchi, B. Schuller, S. Baron-Cohen, O. Golan, S. Boelte, P. Arora, R. Haeb-Umbach, in: INTERSPEECH 2015, 2015.
Source Counting in Speech Mixtures by Nonparametric Bayesian Estimation of an infinite Gaussian Mixture Model
O. Walter, L. Drude, R. Haeb-Umbach, in: 40th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2015), 2015.
Autonomous Learning of Representations
O. Walter, R. Haeb-Umbach, B. Mokbel, B. Paassen, B. Hammer, KI - Kuenstliche Intelligenz (2015) 1–13.
Lexicon Discovery for Language Preservation using Unsupervised Word Segmentation with Pitman-Yor Language Models (FGNT-2015-01)
O. Walter, R. Haeb-Umbach, J. Strunk, N. P. Himmelmann, Lexicon Discovery for Language Preservation Using Unsupervised Word Segmentation with Pitman-Yor Language Models (FGNT-2015-01), 2015.
Aligning training models with smartphone properties in WiFi fingerprinting based indoor localization
M.K. Hoang, J. Schmalenstroeer, R. Haeb-Umbach, in: 40th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2015), 2015.
Spectral Noise Tracking for Improved Nonstationary Noise Robust ASR
A. Chinaev, M. Puels, R. Haeb-Umbach, in: 11. ITG Fachtagung Sprachkommunikation (ITG 2014), 2014.
Source Counting in Speech Mixtures Using a Variational EM Approach for Complexwatson Mixture Models
L. Drude, A. Chinaev, D.H. Tran Vu, R. Haeb-Umbach, in: 39th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), 2014.
Towards Online Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models
L. Drude, A. Chinaev, D.H. Tran Vu, R. Haeb-Umbach, in: 14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014), 2014, pp. 213–217.
Iterative Bayesian Word Segmentation for Unspuervised Vocabulary Discovery from Phoneme Lattices
J. Heymann, O. Walter, R. Haeb-Umbach, B. Raj, in: 39th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), 2014.
Coordinate Mapping Between an Acoustic and Visual Sensor Network in the Shape Domain for a Joint Self-Calibrating Speaker Tracking
F. Jacob, R. Haeb-Umbach, in: 11. ITG Fachtagung Sprachkommunikation (ITG 2014), 2014.
A New Observation Model in the Logarithmic Mel Power Spectral Domain for the Automatic Recognition of Noisy Reverberant Speech
V. Leutnant, A. Krueger, R. Haeb-Umbach, IEEE/ACM Transactions on Audio, Speech, and Language Processing 22 (2014) 95–109.
An Overview of Noise-Robust Automatic Speech Recognition
J. Li, L. Deng, Y. Gong, R. Haeb-Umbach, IEEE Transactions on Audio, Speech and Language Processing 22 (2014) 745–777.
An Evaluation of Unsupervised Acoustic Model Training for a Dysarthric Speech Interface
O. Walter, V. Despotovic, R. Haeb-Umbach, J. Gemmeke, B. Ons, H. Van hamme, in: INTERSPEECH 2014, 2014.
A combined hardware-software approach for acoustic sensor network synchronization
J. Schmalenstroeer, P. Jebramcik, R. Haeb-Umbach, Signal Processing (2014).
A Gossiping Approach to Sampling Clock Synchronization in Wireless Acoustic Sensor Networks
J. Schmalenstroeer, P. Jebramcik, R. Haeb-Umbach, in: 39th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), 2014.
Online Observation Error Model Estimation for Acoustic Sensor Network Synchronization
J. Schmalenstroeer, W. Zhao, R. Haeb-Umbach, in: 11. ITG Fachtagung Sprachkommunikation (ITG 2014), 2014.
GMM-based significance decoding
A.H. Abdelaziz, S. Zeiler, D. Kolossa, V. Leutnant, R. Haeb-Umbach, in: Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference On, 2013, pp. 6827–6831.
MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations
A. Chinaev, R. Haeb-Umbach, in: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 3352–3356.
Improved Single-Channel Nonstationary Noise Tracking by an Optimized MAP-based Postprocessor
A. Chinaev, R. Haeb-Umbach, J. Taghia, R. Martin, in: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 7477–7481.
On the Acoustic Channel Identification in Multi-Microphone Systems via Adaptive Blind Signal Enhancement Techniques
G. Enzner, D. Schmid, R. Haeb-Umbach, in: 21th European Signal Processing Conference (EUSIPCO 2013), 2013.
Unsupervised Word Segmentation from Noisy Input
J. Heymann, O. Walter, R. Haeb-Umbach, B. Raj, in: Automatic Speech Recognition and Understanding Workshop (ASRU 2013), 2013.
Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning
M.K. Hoang, R. Haeb-Umbach, in: 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), 2013, pp. 3721–3725.
The reverb challenge: a common evaluation framework for dereverberation and recognition of reverberant speech
K. Kinoshita, M. Delcroix, T. Yoshioka, T. Nakatani, E. Habets, R. Haeb-Umbach, V. Leutnant, A. Sehr, W. Kellermann, R. Maas, S. Gannot, B. Raj, in: IEEE Workshop on Applications of Signal Processing to Audio and Acoustics , 2013, pp. 22–23.
Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition
V. Leutnant, A. Krueger, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 21 (2013) 1640–1652.
Blind Speech Separation Exploiting Temporal and Spectral Correlations Using Turbo Decoding of 2D-HMMs
D.H. Tran Vu, R. Haeb-Umbach, in: 21th European Signal Processing Conference (EUSIPCO 2013), 2013.
Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation
D.H.T. Vu, R. Haeb-Umbach, in: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 863–867.
Unsupervised Word Discovery from Phonetic Input Using Nested Pitman-Yor Language Modeling
O. Walter, R. Haeb-Umbach, S. Chaudhuri, B. Raj, in: IEEE International Conference on Robotics and Automation (ICRA 2013), 2013.
Hierarchical System for Word Discovery Exploiting DTW-Based Initialization
O. Walter, T. Korthals, R. Haeb-Umbach, B. Raj, in: Automatic Speech Recognition and Understanding Workshop (ASRU 2013), 2013.
A Novel Initialization Method for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01)
O. Walter, J. Schmalenstroeer, R. Haeb-Umbach, A Novel Initialization Method for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01), 2013.
DoA-Based Microphone Array Position Self-Calibration Using Circular Statistic
F. Jacob, J. Schmalenstroeer, R. Haeb-Umbach, in: 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), 2013, pp. 116–120.
Sampling Rate Synchronisation in Acoustic Sensor Networks with a Pre-Trained Clock Skew Error Model
J. Schmalenstroeer, R. Haeb-Umbach, in: 21th European Signal Processing Conference (EUSIPCO 2013), 2013.
Server based indoor navigation using RSSI and inertial sensor information
M.K. Hoang, S. Schmitz, C. Drueke, D.H.T. Vu, J. Schmalenstroeer, R. Haeb-Umbach, in: Positioning Navigation and Communication (WPNC), 2013 10th Workshop On, 2013, pp. 1–6.
A Hidden Markov Model for Indoor User Tracking Based on WiFi Fingerprinting and Step Detection
M.K. Hoang, J. Schmalenstroeer, C. Drueke, D.H. Tran Vu, R. Haeb-Umbach, in: 21th European Signal Processing Conference (EUSIPCO 2013), 2013.
Quality Analysis and Optimization of the MAP-based Noise Power Spectral Density Tracker
A. Chinaev, R. Haeb-Umbach, in: Speech Communication; 10. ITG Symposium; Proceedings., 2012.
Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor
A. Chinaev, A. Krueger, D.H. Tran Vu, R. Haeb-Umbach, in: 37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012), 2012.
Reverberant Speech Recognition
A. Krueger, R. Haeb-Umbach, in: Techniques for Noise Robustness in Automatic Speech Recognition, Wiley, 2012.
Bayesian Feature Enhancement for ASR of Noisy Reverberant Real-World Data
A. Krueger, O. Walter, V. Leutnant, R. Haeb-Umbach, in: Proc. Interspeech, Portland, USA, 2012.
Investigations Into a Statistical Observation Model for Logarithmic Mel Power Spectral Density Features of Noisy Reverberant Speech
V. Leutnant, A. Krueger, R. Haeb-Umbach, Speech Communication; 10. ITG Symposium; Proceedings Of (2012) 1–4.
A Statistical Observation Model For Noisy Reverberant Speech Features and its Application to Robust ASR
V. Leutnant, A. Krueger, R. Haeb-Umbach, in: Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference On, 2012.
Derivation of the Power Compensation Constant in the Observation Model for Reverberant Speech in the Logarithmic Mel Power Spectral Domain
V. Leutnant, A. Krueger, R. Haeb-Umbach, Derivation of the Power Compensation Constant in the Observation Model for Reverberant Speech in the Logarithmic Mel Power Spectral Domain, 2012.
Exploiting Temporal Correlations in Joint Multichannel Speech Separation and Noise Suppression using Hidden Markov Models
D.H. Tran Vu, R. Haeb-Umbach, in: International Workshop on Acoustic Signal Enhancement (IWAENC2012), 2012.
Microphone Array Position Self-Calibration from Reverberant Speech Input
F. Jacob, J. Schmalenstroeer, R. Haeb-Umbach, in: International Workshop on Acoustic Signal Enhancement (IWAENC 2012), 2012.
Smartphone-Based Sensor Fusion for Improved Vehicular Navigation
O. Walter, J. Schmalenstroeer, A. Engler, R. Haeb-Umbach, in: 9th Workshop on Positioning Navigation and Communication (WPNC 2012), 2012.
A Platform for efficient Supply Chain Management Support in Logistics
M. Bevermeier, S. Flanke, R. Haeb-Umbach, J. Stehr, in: International Workshop on Intelligent Transportation (WIT 2011), 2011.
Uncertainty Decoding and Conditional Bayesian Estimation
R. Haeb-Umbach, in: R. Haeb-Umbach, D. Kolossa (Eds.), Robust Speech Recognition of Uncertain or Missing Data, Springer, 2011.
Können Computer sprechen und hören, sollen sie es überhaupt können? Sprachverarbeitung und ambiente Intelligenz
R. Haeb-Umbach, in: Baustelle Informationsgesellschaft Und Universität Heute, Ferdinand Schoeningh Verlag, Paderborn, 2011.
Adaptive Systems for Unsupervised Speaker Tracking and Speech Recognition
T. Herbig, F. Gerl, W. Minker, R. Haeb-Umbach, Evolving Systems 2 (2011) 199–214.
A Model-Based Approach to Joint Compensation of Noise and Reverberation for Speech Recognition
A. Krueger, R. Haeb-Umbach, in: R. Haeb-Umbach, D. Kolossa (Eds.), Robust Speech Recognition of Uncertain or Missing Data, Springer, 2011.
MAP-based estimation of the parameters of non-stationary Gaussian processes from noisy observations
A. Krueger, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 2011, pp. 3596–3599.
Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation
A. Krueger, E. Warsitz, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 19 (2011) 206–219.
Conditional Bayesian Estimation Employing a Phase-Sensitive Observation Model for Noise Robust Speech Recognition
V. Leutnant, R. Haeb-Umbach, in: R. Haeb-Umbach, D. Kolossa (Eds.), Robust Speech Recognition of Uncertain or Missing Data, Springer, 2011.
A versatile Gaussian splitting approach to non-linear state estimation and its application to noise-robust ASR
V. Leutnant, A. Krueger, R. Haeb-Umbach, in: Interspeech 2011, 2011.
On Initial Seed Selection for Frequency Domain Blind Speech Separation
D.H. Tran Vu, R. Haeb-Umbach, in: Interspeech 2011, 2011.
Robust Speech Recognition of Uncertain or Missing Data --- Theory and Applications
D. Kolossa, R. Haeb-Umbach, eds., Robust Speech Recognition of Uncertain or Missing Data --- Theory and Applications, Springer, 2011.
Unsupervised learning of acoustic events using dynamic time warping and hierarchical K-means++ clustering
J. Schmalenstroeer, M. Bartek, R. Haeb-Umbach, in: Interspeech 2011, 2011.
Unsupervised Geometry Calibration of Acoustic Sensor Networks Using Source Correspondences
J. Schmalenstroeer, F. Jacob, R. Haeb-Umbach, M. Hennecke, G.A. Fink, in: Interspeech 2011, 2011.
Investigations into Features for Robust Classification into Broad Acoustic Categories
J. Schmalenstroeer, M. Bartek, R. Haeb-Umbach, in: 37. Deutsche Jahrestagung Fuer Akustik (DAGA 2011), 2011.
Barometric height estimation combined with map-matching in a loosely-coupled Kalman-filter
M. Bevermeier, O. Walter, S. Peschke, R. Haeb-Umbach, in: 7th Workshop on Positioning Navigation and Communication (WPNC 2010), 2010, pp. 128–134.
Model-Based Feature Enhancement for Reverberant Speech Recognition
A. Krueger, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 18 (2010) 1692–1707.
Options for Modelling Temporal Statistical Dependencies in an Acoustic Model for ASR
V. Leutnant, R. Haeb-Umbach, in: 36. Deutsche Jahrestagung Fuer Akustik (DAGA 2010), 2010.
On the Exploitation of Hidden Markov Models and Linear Dynamic Models in a Hybrid Decoder Architecture for Continuous Speech Recognition
V. Leutnant, R. Haeb-Umbach, in: Interspeech 2010, 2010.
Ungrounded Independent Non-Negative Factor Analysis
B. Raj, K.W. Wilson, A. Krueger, R. Haeb-Umbach, in: Interspeech 2010, 2010.
An EM Approach to Integrated Multichannel Speech Separation and Noise Suppression
D.H. Tran Vu, R. Haeb-Umbach, in: International Workshop on Acoustic Echo and Noise Control (IWAENC 2010), 2010.
Blind speech separation employing directional statistics in an Expectation Maximization framework
D.H. Tran Vu, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), 2010, pp. 241–244.
Online Diarization of Streaming Audio-Visual Data for Smart Environments
J. Schmalenstroeer, R. Haeb-Umbach, IEEE Journal of Selected Topics in Signal Processing 4 (2010) 845–856.
Robust vehicle localization based on multi-level sensor fusion and online parameter estimation
Alle Publikationen anzeigen
M. Bevermeier, S. Peschke, R. Haeb-Umbach, in: 6th Workshop on Positioning Navigation and Communication (WPNC 2009), 2009, pp. 235–242.