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i-Vector Modeling of Speech Attributes for Automatic Foreign Accent Recognition.

, , , , and . IEEE ACM Trans. Audio Speech Lang. Process., 24 (1): 29-41 (2016)

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Nuclei instance segmentation from histopathology images using Bayesian dropout based deep learning., , , and . BMC Bioinform., 23 (1): 162 (December 2022)Dialect levelling in Finnish: a universal speech attribute approach., , , , , , and . INTERSPEECH, page 2165-2169. ISCA, (2014)Boosting universal speech attributes classification with deep neural network for foreign accent characterization., , , , and . INTERSPEECH, page 408-412. ISCA, (2015)Out-of-Set i-Vector Selection for Open-set Language Identification., , and . Odyssey, page 303-310. ISCA, (2016)Gender Classification Using Single Frontal Image Per Person: Combination of Appearance and Geometric Based Features., , and . ICPR, page 1192-1195. IEEE Computer Society, (2010)Factors affecting i-vector based foreign accent recognition: A case study in spoken Finnish., , and . Speech Commun., (2015)i-Vector Modeling of Speech Attributes for Automatic Foreign Accent Recognition., , , , and . IEEE ACM Trans. Audio Speech Lang. Process., 24 (1): 29-41 (2016)Foreign accent detection from spoken Finnish using i-vectors., , and . INTERSPEECH, page 79-83. ISCA, (2013)Introducing attribute features to foreign accent recognition., , , , and . ICASSP, page 5332-5336. IEEE, (2014)