Abstract
This paper presents an experimental German speech synthesis system. As in case of a Czech text-to-speech system ARTIC, statistical approach (using hidden Markov models) was employed to build a speech segment database. This approach was confirmed to be language independent and it was shown to be capable of designing a quality database that led to an intelligible synthetic speech of a high quality. Some experiments with clustering the similar speech contexts were performed to enhance the quality of the synthetic speech. Our results show the superiority of phoneme-level clustering to subphoneme-level one.
This research was supported by the project no. MSM235200004 of the Ministry of Education of Czech Republic and the firm SpeechTech.
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© 2002 Springer-Verlag Berlin Heidelberg
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Matoušek, J., Tihelka, D., Psutka, J., Hesová, J. (2002). German and Czech Speech Synthesis Using HMM-Based Speech Segment Database. In: Sojka, P., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2002. Lecture Notes in Computer Science(), vol 2448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46154-X_24
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DOI: https://doi.org/10.1007/3-540-46154-X_24
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