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

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

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.
LibreCat: /record/11864

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

Approaches to Iterative Speech Feature Enhancement and Recognition
S. Windmann, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 17 (2009) 974–984.
LibreCat: /record/11937
DOI: 10.1109/TASL.2009.2014894

Modeling the dynamics of speech and noise for speech feature enhancement in ASR
S. Windmann, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008), 2008, pp. 4409–4412.
LibreCat: /record/11939
DOI: 10.1109/ICASSP.2008.4518633