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Better Phoneme Recognisers Lead to Better Phoneme Posteriorgrams for Search on Speech? An Experimental Analysis.

, , and . IberSPEECH, volume 10077 of Lecture Notes in Computer Science, page 128-137. (2016)

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An adaptive threshold computation for unsupervised speaker segmentation., , and . INTERSPEECH, page 840-843. ISCA, (2009)Creating expressive synthetic voices by unsupervised clustering of audiobooks., , , and . INTERSPEECH, page 3380-3384. ISCA, (2015)Influence of speaker de-identification in depression detection., , , , , and . IET Signal Processing, 11 (9): 1023-1030 (2017)Converted Mel-Cepstral Coefficients for Gender Variability Reduction in Query-by-Example Spoken Document Retrieval., and . IberSPEECH, page 82-86. ISCA, (2018)Efficient query-by-example spoken document retrieval combining phone multigram representation and dynamic time warping., , and . Inf. Process. Manage., 56 (1): 43-60 (2019)Piecewise linear definition of transformation functions for speaker de-identification., , , , , and . SPLINE, page 1-5. IEEE, (2016)Better Phoneme Recognisers Lead to Better Phoneme Posteriorgrams for Search on Speech? An Experimental Analysis., , and . IberSPEECH, volume 10077 of Lecture Notes in Computer Science, page 128-137. (2016)Comparison of ALBAYZIN query-by-example spoken term detection 2012 and 2014 evaluations., , , , and . EURASIP J. Audio, Speech and Music Processing, (2016)Albayzín-2014 evaluation: audio segmentation and classification in broadcast news domains., , , , , , , , , and 1 other author(s). EURASIP J. Audio, Speech and Music Processing, (2015)Reversible speaker de-identification using pre-trained transformation functions., , , , , and . Computer Speech & Language, (2017)