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.

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 

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 

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 

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 

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., &; 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 

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 

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 

Ion, V., &; Haeb-Umbach, R. (2006). An Inexpensive Packet Loss Compensation Scheme for Distributed Speech Recognition Based on Soft-Features. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006) (Vol. 1, p. I).https://doi.org/10.1109/ICASSP.2006.1659984 

Ion, V., &; Haeb-Umbach, R. (2006). Uncertainty decoding for distributed speech recognition over error-prone networks. Speech Communication, 48(11), 1435–1446.https://doi.org/10.1016/j.specom.2006.03.007 

Ion, V., &; Haeb-Umbach, R. (2005). A Comparison of Soft-Feature Distributed Speech Recognition with Candidate Codecs for Speech Enabled Mobile Services. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005) (Vol. 1, pp. 333–336).https://doi.org/10.1109/ICASSP.2005.1415118 

Warsitz, E., &; Haeb-Umbach, R. (2004). Robust speaker direction estimation with particle filtering. In IEEE Workshop on Multimedia Signal Processing (MMSP 2004) (pp. 367–370).https://doi.org/10.1109/MMSP.2004.1436569 

Müller, W., Schäfer, R., &; Bleul, S. (2004). Interactive Multimodal User Interfaces for Mobile Devices. Proceedings of HICCS-37. 37th Annual Hawaii International Conference on System Sciences, Waikoloa, HI, USA.https://doi.org/10.1109/HICSS.2004.1265674 

Haeb-Umbach, R. (2001). Automatic generation of phonetic regression class trees for MLLR adaptation. IEEE Transactions on Speech and Audio Processing, 9(3), 299–302.https://doi.org/10.1109/89.906003 

Lieb, M., &; Haeb-Umbach, R. (2000). LDA derived cepstral trajectory filters in adverse environmental conditions. In IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2000) (Vol. 2, pp. - vol.2).https://doi.org/10.1109/ICASSP.2000.859157