Table of Contents

• The NIST speaker recognition evaluationsAlvin F. Martin. [doi]
• Being deep and being dynamic - new-generation models and methodology for advancing speech technologyLi Deng. [doi]
• The role of proper scoring rules in training and evaluating probabilistic speaker and language recognizersNiko Brümmer. [doi]
• A small footprint i-vector extractorPatrick Kenny. 1-6 [doi]
• Memory and computation effective approaches for i - vector extractionSandro Cumani, Pietro Laface, Vasileios Vasilakakis. 7-13 [doi]
• A hybrid factor analysis and probabilistic PCA-based system for dictionary learning and encoding for robust speaker recognitionSrikanth R. Madikeri. 14-20 [doi]
• On exploring the similarity and fusion of i-vector and sparse representation based speaker verification systemsHaris B. C., Rohit Sinha. 21-27 [doi]
• PLDA based speaker recognition on short utterancesAhilan Kanagasundaram, Robbie Vogt, David Dean, Sridha Sridharan. 28-33 [doi]
• PLDA based speaker verification with weighted LDA techniquesAhilan Kanagasundaram, David Dean, Sridha Sridharan, Robbie Vogt. 34-38 [doi]
• Dataset shift in PLDA based speaker verificationCarlos Vaquero. 39-46 [doi]
• Bayesian adaptation of PLDA based speaker recognition to domains with scarce development dataJesús A. Villalba, Eduardo Lleida. 47-54 [doi]
• Source normalization for language-independent speaker recognition using i-vectorsMitchell McLaren, Miranti Indar Mandasari, David A. van Leeuwen. 55-61 [doi]
• Database selection for forensic voice comparisonGeoffrey Stewart Morrison, Felipe Ochoa, Tharmarajah Thiruvaran. 62-77 [doi]
• Voice source features for forensic voice comparison - an evaluation of the GLOTTEX software packageEwald Enzinger, Cuiling Zhang, Geoffrey Stewart Morrison. 78-85 [doi]
• Comparison of speaker recognition systems on a real forensic benchmarkYosef A. Solewicz, Timo Becker, Gaëlle Jardine, Stefan G. Gfrörer. 86-91 [doi]
• Factor analysis of mixture of auto-associative neural networks for speaker verificationSri Garimella, Hynek Hermansky. 92-97 [doi]
• Adaptation transforms of auto-associative neural networks as features for speaker verificationSamuel Thomas, Sri Harish Reddy Mallidi, Sriram Ganapathy, Hynek Hermansky. 98-104 [doi]
• Bottleneck features for speaker recognitionSibel Yaman, Jason W. Pelecanos, Ruhi Sarikaya. 105-108 [doi]
• Preliminary investigation of Boltzmann machine classifiers for speaker recognitionThemos Stafylakis, Patrick Kenny, Mohammed Senoussaoui, Pierre Dumouchel. 109-116 [doi]
• First attempt of boltzmann machines for speaker verificationMohammed Senoussaoui, Najim Dehak, Patrick Kenny, Réda Dehak, Pierre Dumouchel. 117-121 [doi]
• Online two speaker diarizationHagai Aronowitz, Yosef A. Solewicz, Orith Toledo-Ronen. 122-129 [doi]
• On the use of agglomerative and spectral clustering in speaker diarization of meetingsJordi Luque, Javier Hernando. 130-137 [doi]
• Generalized Viterbi-based models for time-series segmentation applied to speaker diarizationItshak Lapidot, Jean-François Bonastre. 138-145 [doi]
• A global optimization framework for speaker diarizationMickael Rouvier, Sylvain Meignier. 146-150 [doi]
• Cisco's speaker segmentation and recognition systemSashin Kajarekar, Aparna Khare, Matthias Paulik, Neha Agrawal, Panchi Panchapagesan, Ananth Sankar, Satish Gannu. 151-156 [doi]
• Variance-spectra based normalization for i-vector standard and probabilistic linear discriminant analysisPierre-Michel Bousquet, Anthony Larcher, Driss Matrouf, Jean-François Bonastre, Oldrich Plchot. 157-164 [doi]
• Utterance partitioning with acoustic vector resampling for i-vector based speaker verificationWei Rao, Man-Wai Mak. 165-171 [doi]
• Study on the effects of intrinsic variation using i-vectors in text-independent speaker verificationSheng Chen, Mingxing Xu, Emlyn Pratt. 172-179 [doi]
• Exploring the impact of advanced front-end processing on NIST speaker recognition microphone tasksWilliam M. Campbell, Douglas E. Sturim, Bengt J. Borgström, Robert B. Dunn, Alan McCree, Thomas F. Quatieri, Douglas A. Reynolds. 180-186 [doi]
• Linear prediction modulation filtering for speaker recognition of reverberant speechBengt J. Borgström, Alan McCree. 187-193 [doi]
• Evaluation of spoken language recognition technology using broadcast speech: performance and challengesLuis Javier Rodríguez-Fuentes, Amparo Varona, Mireia Díez, Mikel Peñagarikano, Germán Bordel. 194-201 [doi]
• New resources for recognition of confusable linguistic varieties: the LRE11 corpusStephanie Strassel, Kevin Walker, Karen Jones, David Graff, Christopher Cieri. 202-208 [doi]
• The MITLL NIST LRE 2011 language recognition systemElliot Singer, Pedro A. Torres-Carrasquillo, Douglas A. Reynolds, Alan McCree, Fred Richardson, Najim Dehak, Douglas E. Sturim. 209-215 [doi]
• Description and analysis of the Brno276 system for LRE2011Niko Brümmer, Sandro Cumani, Ondrej Glembek, Martin Karafiát, Pavel Matejka, Jan Pesán, Oldrich Plchot, Mehdi Soufifar, Edward de Villiers, Jan Cernocký. 216-223 [doi]
• A linguistic data acquisition front-end for language recognition evaluationGang Liu, Chi Zhang, John H. L. Hansen. 224-228 [doi]
• Feature extraction using 2-d autoregressive models for speaker recognitionSriram Ganapathy, Samuel Thomas, Hynek Hermansky. 229-235 [doi]
• Regularization of all-pole models for speaker verification under additive noiseCemal Hanilçi, Tomi Kinnunen, Rahim Saeidi, Jouni Pohjalainen, Paavo Alku, Figen Ertas. 236-242 [doi]
• Factor analysis of acoustic features using a mixture of probabilistic principal component analyzers for robust speaker verificationTaufiq Hasan, John H. L. Hansen. 243-247 [doi]
• Exemplar-based sparse representation and sparse discrimination for noise robust speaker identificationRahim Saeidi, Antti Hurmalainen, Tuomas Virtanen, David A. van Leeuwen. 248-255 [doi]
• On the use of asymmetric-shaped tapers for speaker verification using i-vectorsMd. Jahangir Alam, Patrick Kenny, Douglas D. O'Shaughnessy. 256-262 [doi]
• The effect of target/non-target age difference on speaker recognition performanceGeorge R. Doddington. 263-267 [doi]
• Variational Bayes logistic regression as regularized fusion for NIST SRE 2010Ville Hautamäki, Kong-Aik Lee, Anthony Larcher, Tomi Kinnunen, Bin Ma, Haizhou Li. 268-274 [doi]
• The 2011 BEST speaker recognition interim assessmentCraig S. Greenberg, Alvin F. Martin, Mark A. Przybocki. 275-282 [doi]
• The REPERE challenge: finding people in a multimodal contextJuliette Kahn, Olivier Galibert, Matthieu Carré, Aude Giraudel, Philippe Joly, Ludovic Quintard. 283-290 [doi]
• The RATS radio traffic collection systemKevin Walker, Stephanie Strassel. 291-297 [doi]
• Effects of audio and ASR quality on cepstral and high-level speaker verification systemsAndreas Stolcke, Martin Graciarena, Luciana Ferrer. 298-303 [doi]
• Audio context recognition in variable mobile environments from short segments using speaker and language recognizersTomi Kinnunen, Rahim Saeidi, Jussi Leppänen, Jukka Saarinen. 304-311 [doi]
• Text dependent speaker verification using a small development setHagai Aronowitz. 312-316 [doi]
• A unified approach for audio characterization and its application to speaker recognitionLuciana Ferrer, Lukás Burget, Oldrich Plchot, Nicolas Scheffer. 317-323 [doi]
• Mean shift algorithm for exponential families with applications to speaker clusteringThemos Stafylakis, Vassilios Katsouros, Patrick Kenny, Pierre Dumouchel. 324-329 [doi]
• Speaker vectors from subspace Gaussian mixture model as complementary features for language identificationOldrich Plchot, Martin Karafiát, Niko Brümmer, Ondrej Glembek, Pavel Matejka, Edward de Villiers, Jan Cernocký. 330-333 [doi]
• Complementary combination in i-vector level for language recognitionZhiyi Li, Wei-Qiang Zhang, Liang He, Jia Liu. 334-337 [doi]
• Bhattacharyya-based GMM-SVM system with adaptive relevance factor for pair language recognitionChang Huai You, Haizhou Li, Eliathamby Ambikairajah, Kong-Aik Lee, Bin Ma. 338-345 [doi]
• Fusing language information from diverse data sources for phonotactic language recognitionMohamed Faouzi BenZeghiba, Jean-Luc Gauvain, Lori Lamel. 346-352 [doi]