Improvements of Hungarian Hidden Markov Model-based text-to-speech synthesis

Tóth Bálint and Németh Géza: Improvements of Hungarian Hidden Markov Model-based text-to-speech synthesis. In: Acta cybernetica, (19) 4. pp. 715-731. (2010)

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Statistical parametric, especially Hidden Markov Model-based, text-to-speech (TTS) synthesis has received much attention recently. The quality of HMM-based speech synthesis approaches that of the state-of-the-art unit selection systems and possesses numerous favorable features, e.g. small runtime footprint, speaker interpolation, speaker adaptation. This paper presents the improvements of a Hungarian HMM-based speech synthesis system, including speaker dependent and adaptive training, speech synthesis with pulse-noise and mixed excitation. Listening tests and their evaluation are also described.

Item Type: Article
Journal or Publication Title: Acta cybernetica
Date: 2010
Volume: 19
Number: 4
ISSN: 0324-721X
Page Range: pp. 715-731
Language: English
Place of Publication: Szeged
Event Title: Conference on Hungarian Computational Linguistics (7.) (2010) (Szeged)
Related URLs:
Uncontrolled Keywords: Számítástechnika, Nyelvészet - számítógép alkalmazása
Additional Information: Bibliogr.: p. 729-731. ; összefoglalás angol nyelven
Subjects: 01. Natural sciences
01. Natural sciences > 01.02. Computer and information sciences
06. Humanities
06. Humanities > 06.02. Languages and Literature
Date Deposited: 2016. Oct. 15. 12:24
Last Modified: 2022. Jun. 17. 11:17

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