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Combining i-vector representation and structured neural networks for rapid adaptation.

, , and . ICASSP, page 5000-5004. IEEE, (2016)

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Cross-lingual Style Transfer with Conditional Prior VAE and Style Loss., , , , , and . INTERSPEECH, page 4586-4590. ISCA, (2022)I-vector estimation using informative priors for adaptation of deep neural networks., , and . INTERSPEECH, page 2872-2876. ISCA, (2015)Cambridge university transcription systems for the multi-genre broadcast challenge., , , , , , , and . ASRU, page 639-646. IEEE, (2015)Combining i-vector representation and structured neural networks for rapid adaptation., , and . ICASSP, page 5000-5004. IEEE, (2016)Speaker diarisation and longitudinal linking in multi-genre broadcast data., , , , , , , and . ASRU, page 660-666. IEEE, (2015)Prosodic Representation Learning and Contextual Sampling for Neural Text-to-Speech., , , , , , and . ICASSP, page 6573-6577. IEEE, (2021)Controllable Emphasis with zero data for text-to-speech., , , , , , , , , and 4 other author(s). SSW, page 113-119. ISCA, (2023)An investigation into speaker informed DNN front-end for LVCSR., , and . ICASSP, page 4300-4304. IEEE, (2015)Camp: A Two-Stage Approach to Modelling Prosody in Context., , , , , , , , and . ICASSP, page 6578-6582. IEEE, (2021)The development of the cambridge university alignment systems for the multi-genre broadcast challenge., , , , , , , and . ASRU, page 647-653. IEEE, (2015)