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Depression Detection Using Automatic Transcriptions of De-Identified Speech.

, , , and . INTERSPEECH, page 3157-3161. ISCA, (2017)

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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)Problemática de la recogida y anotación de una base de datos oral para el gallego., , , and . Procesamiento del Lenguaje Natural, (2001)Speaker Segmentation., and . Encyclopedia of Biometrics, Springer US, (2015)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)Converted Mel-Cepstral Coefficients for Gender Variability Reduction in Query-by-Example Spoken Document Retrieval., and . IberSPEECH, page 82-86. ISCA, (2018)Estudio sobre el impacto del corpus de entrenamiento del modelo de lenguaje en las prestaciones de un reconocedor de habla., , , and . Procesamiento del Lenguaje Natural, (2018)Influence of speaker de-identification in depression detection., , , , , and . IET Signal Processing, 11 (9): 1023-1030 (2017)Performance analysis of Distributed Speech Recognition over IP networks on the AURORA database., , , , and . ICASSP, page 3820-3823. IEEE, (2002)