Improvements of Hungarian Hidden Markov Model-based text-to-speech synthesis
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 fo...
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| Format: | Article |
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2010
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| Series: | Acta cybernetica
19 No. 4 |
| Kulcsszavak: | Számítástechnika, Nyelvészet - számítógép alkalmazása |
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| Online Access: | http://acta.bibl.u-szeged.hu/12890 |
| Summary: | 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. |
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| Physical Description: | 715-731 |
| ISSN: | 0324-721X |