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dc.contributor.author Louw, Johannes A
dc.contributor.author Moodley, Avashlin
dc.date.accessioned 2019-04-12T08:51:53Z
dc.date.available 2019-04-12T08:51:53Z
dc.date.issued 2016-12
dc.identifier.citation Louw, J.A. & Moodley, A. 2016. Speaker specific phrase break modeling with conditional random fields for text-to-speech. In: 2016 Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference, 30 November - 2 December 2016, Stellenbosch, South Africa en_US
dc.identifier.issn 978-1-5090-3334
dc.identifier.uri https://ieeexplore.ieee.org/document/7813163
dc.identifier.uri DOI: 10.1109/RoboMech.2016.7813163
dc.identifier.uri http://hdl.handle.net/10204/10966
dc.description Presented in: 2016 Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference, 30 November - 2 December 2016, Stellenbosch, South Africa. Due to copyright restrictions, the attached PDF file only contains the abstract of the full-text item. For access to the full-text item, please consult the publisher's website. While waiting for the post-print or published PDF document from the publisher en_US
dc.description.abstract In this paper we present a new cascading conditional random field based phrase break model for text-to-speech systems, trained on the speaker specific acoustic data that the text-to-speech voices are trained on. The training phase does not require any manually labeled phrase break tags, as these are derived directly from the speaker specific recordings used for building the synthetic voices. We present objective evaluations on various corpora, and show that the proposed model compares well with state-of-the-art data-driven phrase break models, with the added benefit of being in a unified framework. en_US
dc.language.iso en en_US
dc.relation.ispartofseries Workflow;18124
dc.subject Text-to-speech systems en_US
dc.subject Phrase breaks en_US
dc.subject Prosodic phrasing en_US
dc.title Speaker specific phrase break modeling with conditional random fields for text-to-speech en_US
dc.type Presentation en_US


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