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Von Mises-Fisher Models in the Total Variability Subspace for Language Recognition., , , and . IEEE Signal Process. Lett., 18 (12): 705-708 (2011)Improved language recognition using better phonetic decoders and fusion with MFCC and SDC features., , , , , and . INTERSPEECH, page 194-197. ISCA, (2007)An end-to-end approach to language identification in short utterances using convolutional neural networks., , , , and . INTERSPEECH, page 403-407. ISCA, (2015)Addressing database mismatch in forensic speaker recognition with Ahumada III: a public real-casework database in Spanish., , , and . INTERSPEECH, page 1493-1496. ISCA, (2008)On the Use of Factor Analysis with Restricted Target Data in Speaker Verification., , , , and . Odyssey, page 20. ISCA, (2010)Improving the PLDA based speaker verification in limited microphone data conditions., , , , , and . INTERSPEECH, page 3674-3678. ISCA, (2013)Improving short utterance based i-vector speaker recognition using source and utterance-duration normalization techniques., , , , , and . INTERSPEECH, page 2465-2469. ISCA, (2013)Automatic language identification using long short-term memory recurrent neural networks., , , , and . INTERSPEECH, page 2155-2159. ISCA, (2014)Score-level compensation of extreme speech duration variability in speaker verification., , , and . INTERSPEECH, page 374-377. ISCA, (2010)Exploring PPRLM performance for NIST 2005 Language Recognition Evaluation., , , , and . Odyssey, page 1-6. IEEE, (2006)