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 

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 

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).

Leutnant, V., Krueger, A., &; Haeb-Umbach, R. (2013). Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition. IEEE Transactions on Audio, Speech, and Language Processing, 21(8), 1640–1652.https://doi.org/10.1109/TASL.2013.2258013 

Vu, D. H. T., &; Haeb-Umbach, R. (2013). 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) (pp. 863–867).https://doi.org/10.1109/ICASSP.2013.6637771 

Chinaev, A., Krueger, A., Tran Vu, D. H., &; Haeb-Umbach, R. (2012). Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor. In 37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012).

Leutnant, V., Krueger, A., &; Haeb-Umbach, R. (2012). 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.

Krueger, A., Warsitz, E., &; Haeb-Umbach, R. (2011). Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation. IEEE Transactions on Audio, Speech, and Language Processing, 19(1), 206–219.https://doi.org/10.1109/TASL.2010.2047324 

Fischer, K., Foth, K., Rohlfing, K., &; Wrede, B. (2011). Mindful tutors: Linguistic choice and action demonstration in speech to infants and a simulated robot. Interaction Studies, 12(1), 134–161.https://doi.org/10.1075/is.12.1.06fis 

Krueger, A., &; Haeb-Umbach, R. (2010). Model-Based Feature Enhancement for Reverberant Speech Recognition. IEEE Transactions on Audio, Speech, and Language Processing, 18(7), 1692–1707.https://doi.org/10.1109/TASL.2010.2049684 

Tran Vu, D. H., &; Haeb-Umbach, R. (2010). Blind speech separation employing directional statistics in an Expectation Maximization framework. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010) (pp. 241–244).https://doi.org/10.1109/ICASSP.2010.5495994 

Schmalenstroeer, J., &; Haeb-Umbach, R. (2010). Online Diarization of Streaming Audio-Visual Data for Smart Environments. IEEE Journal of Selected Topics in Signal Processing, 4(5), 845–856.https://doi.org/10.1109/JSTSP.2010.2050519 

Windmann, S., &; Haeb-Umbach, R. (2009). Approaches to Iterative Speech Feature Enhancement and Recognition. IEEE Transactions on Audio, Speech, and Language Processing, 17(5), 974–984.https://doi.org/10.1109/TASL.2009.2014894 

Windmann, S., &; Haeb-Umbach, R. (2009). Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition. IEEE Transactions on Audio, Speech, and Language Processing, 17(8), 1577–1590.https://doi.org/10.1109/TASL.2009.2023172 

Vollmer, A.-L., Lohan, K. S., Fischer, K., Nagai, Y., Pitsch, K., Fritsch, J., Rohlfing, K., &; Wrede, B. (2009). People modify their tutoring behavior in robot-directed interaction for action learning. Development and Learning, 2009. ICDL 2009. IEEE 8th International Conference on Development and Learning, 1–6.https://doi.org/10.1109/DEVLRN.2009.5175516 

Ion, V., &; Haeb-Umbach, R. (2008). A Novel Uncertainty Decoding Rule With Applications to Transmission Error Robust Speech Recognition. IEEE Transactions on Audio, Speech, and Language Processing, 16(5), 1047–1060.https://doi.org/10.1109/TASL.2008.925879 

Warsitz, E., Krueger, A., &; Haeb-Umbach, R. (2008). Speech enhancement with a new generalized eigenvector blocking matrix for application in a generalized sidelobe canceller. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008) (pp. 73–76).https://doi.org/10.1109/ICASSP.2008.4517549 

Windmann, S., &; Haeb-Umbach, R. (2008). Modeling the dynamics of speech and noise for speech feature enhancement in ASR. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008) (pp. 4409–4412).https://doi.org/10.1109/ICASSP.2008.4518633 

Lohse, M., Rohlfing, K., Wrede, B., &; Sagerer, G. (2008). “Try something else!”https://doi.org/10.1109/ROBOT.2008.4543743__— When users change their discursive behavior in human-robot interaction. 3481–3486.https://doi.org/10.1109/ROBOT.2008.4543743