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1890 Publications
2014 | Book | LibreCat-ID: 10756
A. I. Esparcia-Alc{\’a}zar et al., Applications of Evolutionary Computation - 17th European Conference, EvoApplications, vol. 8602. Granada, Spain: Springer, 2014.
LibreCat
2014 | Conference Paper | LibreCat-ID: 10773
H. Ghasemzadeh Mohammadi, P.-E. Gaillardon, M. Yazdani, and G. De Micheli, “Fast process variation analysis in nano-scaled technologies using column-wise sparse parameter selection,” in 2014 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH), 2014, pp. 163–168.
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| DOI
2014 | Conference Paper | LibreCat-ID: 11746 | 
A. Chinaev, M. Puels, and R. Haeb-Umbach, “Spectral Noise Tracking for Improved Nonstationary Noise Robust ASR,” in 11. ITG Fachtagung Sprachkommunikation (ITG 2014), 2014.
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2014 | Conference Paper | LibreCat-ID: 11752 |
L. Drude, A. Chinaev, D. H. Tran Vu, and R. Haeb-Umbach, “Source Counting in Speech Mixtures Using a Variational EM Approach for Complexwatson Mixture Models,” in 39th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), 2014.
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2014 | Conference Paper | LibreCat-ID: 11753 |
L. Drude, A. Chinaev, D. H. Tran Vu, and R. Haeb-Umbach, “Towards Online Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models,” in 14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014), 2014, pp. 213–217.
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2014 | Conference Paper | LibreCat-ID: 11814 |
J. Heymann, O. Walter, R. Haeb-Umbach, and B. Raj, “Iterative Bayesian Word Segmentation for Unspuervised Vocabulary Discovery from Phoneme Lattices,” in 39th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), 2014.
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2014 | Conference Paper | LibreCat-ID: 11831 |
F. Jacob and R. Haeb-Umbach, “Coordinate Mapping Between an Acoustic and Visual Sensor Network in the Shape Domain for a Joint Self-Calibrating Speaker Tracking,” in 11. ITG Fachtagung Sprachkommunikation (ITG 2014), 2014.
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2014 | Journal Article | LibreCat-ID: 11861
V. Leutnant, A. Krueger, and R. Haeb-Umbach, “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, vol. 22, no. 1, pp. 95–109, 2014.
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