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.
LibreCat: /record/48275

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 
LibreCat: /record/26770
DOI: 10.21437/interspeech.2021-1177

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 
LibreCat: /record/11813
DOI: 10.1109/ICASSP.2015.7178933

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 
LibreCat: /record/11861
DOI: 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 
LibreCat: /record/11867
DOI: 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 
LibreCat: /record/11716
DOI: 10.1109/ICASSP.2013.6638984

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 
LibreCat: /record/11862
DOI: 10.1109/TASL.2013.2258013

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.
LibreCat: /record/11864

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 
LibreCat: /record/11846
DOI: 10.1109/TASL.2010.2049684

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 
LibreCat: /record/11937
DOI: 10.1109/TASL.2009.2014894