| Application-independent evaluation of speaker detection N Brümmer, J Du Preez Computer Speech & Language 20 (2-3), 230-275, 2006 | 851 | 2006 |
| Support vector machines versus fast scoring in the low-dimensional total variability space for speaker verification. N Dehak, R Dehak, P Kenny, N Brümmer, P Ouellet, P Dumouchel Interspeech 9, 1559-1562, 2009 | 506 | 2009 |
| Fusion of heterogeneous speaker recognition systems in the STBU submission for the NIST speaker recognition evaluation 2006 N Brummer, L Burget, J Cernocky, O Glembek, F Grezl, M Karafiat, ... IEEE Transactions on Audio, Speech, and Language Processing 15 (7), 2072-2084, 2007 | 330 | 2007 |
| An introduction to application-independent evaluation of speaker recognition systems DA Van Leeuwen, N Brümmer Speaker classification I: Fundamentals, features, and methods, 330-353, 2007 | 271 | 2007 |
| The bosaris toolkit: Theory, algorithms and code for surviving the new dcf N Brümmer, E De Villiers arXiv preprint arXiv:1304.2865, 2013 | 248 | 2013 |
| Discriminatively trained probabilistic linear discriminant analysis for speaker verification L Burget, O Plchot, S Cumani, O Glembek, P Matějka, N Brümmer 2011 IEEE international conference on acoustics, speech and signal …, 2011 | 230 | 2011 |
| The speaker partitioning problem. N Brümmer, E De Villiers Odyssey, 34, 2010 | 220 | 2010 |
| The RedDots data collection for speaker recognition KA Lee, A Larcher, G Wang, P Kenny, N Brümmer, D Van Leeuwen, ... Interspeech 2015, 2015 | 188 | 2015 |
| Comparison of scoring methods used in speaker recognition with joint factor analysis O Glembek, L Burget, N Dehak, N Brummer, P Kenny 2009 IEEE International Conference on Acoustics, Speech and Signal …, 2009 | 175 | 2009 |
| On calibration of language recognition scores N Brummer, DA Van Leeuwen 2006 IEEE Odyssey-The Speaker and Language Recognition Workshop, 1-8, 2006 | 173 | 2006 |
| Measuring, refining and calibrating speaker and language information extracted from speech N Brummer Stellenbosch: University of Stellenbosch, 2010 | 157 | 2010 |
| Unsupervised domain adaptation for i-vector speaker recognition D Garcia-Romero, A McCree, S Shum, N Brummer, C Vaquero Proceedings of Odyssey: The Speaker and Language Recognition Workshop 8, 2014 | 151 | 2014 |
| The BOSARIS toolkit user guide: Theory, algorithms and code for binary classifier score processing N Brümmer, E De Villiers Documentation of BOSARIS toolkit 24, 2011 | 116 | 2011 |
| Mixture of PLDA Models in i-vector Space for Gender-Independent Speaker Recognition. M Senoussaoui, P Kenny, N Brümmer, E De Villiers, P Dumouchel Interspeech, 25-28, 2011 | 112 | 2011 |
| Pairwise Discriminative Speaker Verification in the-Vector Space S Cumani, N Brümmer, L Burget, P Laface, O Plchot, V Vasilakakis IEEE Transactions on Audio, Speech, and Language Processing 21 (6), 1217-1227, 2013 | 95 | 2013 |
| Fast discriminative speaker verification in the i-vector space S Cumani, N Brümmer, L Burget, P Laface 2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011 | 66 | 2011 |
| Towards fully Bayesian speaker recognition: Integrating out the between-speaker covariance J Villalba, N Brummer Proc. InterSpeech, Florence, Italy, 505-508, 2011 | 64 | 2011 |
| Focal multi-class: Toolkit for evaluation, fusion and calibration of multi-class recognition scorestutorial and user manual N Brümmer Software available at http://sites. google. com/site/nikobrummer …, 2007 | 60 | 2007 |
| Channel-dependent gmm and multi-class logistic regression models for language recognition DA Van Leeuwen, N Brummer 2006 IEEE Odyssey-The Speaker and Language Recognition Workshop, 1-8, 2006 | 59 | 2006 |
| Discriminative acoustic language recognition via channel-compensated GMM statistics. N Brümmer, A Strasheim, V Hubeika, P Matejka, L Burget, O Glembek Interspeech, 2187-2190, 2009 | 51 | 2009 |
Lukas BurgetBrno University of TechnologyVerified email at fit.vutbr.cz
