Abstract
In this paper, automatic segmentation of parasitic speech sounds in speech corpora for text-to-speech (TTS) synthesis is presented. The automatic segmentation is, beside the automatic detection of the presence of such sounds in speech corpora, an important step in the precise localisation of parasitic sounds in speech corpora. The main goal of this study is to find out whether the segmentation of these sounds is accurate enough to enable cutting the sounds out of synthetic speech or explicit modelling of these sounds during synthesis. HMM-based classifier was employed to detect the parasitic sounds and to find the boundaries between these sounds and the surrounding phones simultaneously. The results show that the automatic segmentation of parasitic sounds is comparable to the segmentation of other phones, which indicates that the cutting out or the explicit usage of parasitic sounds should be possible.
This research has been supported by the Grant Agency of the Czech Republic, project No. GAČR 102/09/0989.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Tihelka, D., Romportl, J.: Exploring Automatic Similarity Measures for Unit Selection Tuning. In: Proceedings of Interspeech, Brighton, Great Britain, pp. 736–739 (2009)
Matoušek, J., Skarnitzl, R., Machač, P., Trmal, J.: Identification and Automatic Detection of Parasitic Speech Sounds. In: Proceedings of Interspeech, Brighton, Great Beritain, pp. 876–879 (2009)
Matoušek, J., Tihelka, D., Romportl, J.: Current State of Czech Text-to-Speech System ARTIC. In: Sojka, P., Kopeček, I., Pala, K. (eds.) TSD 2006. LNCS (LNAI), vol. 4188, pp. 439–446. Springer, Heidelberg (2006)
Skarnitzl, R.: Acoustic Categories of Nonmodal Phonation in the Context of the Czech Conjunction “a”. In: Palková, Z., Veroňková, J. (eds.) AUC Philologica 1/2004, Phonetica Pragensia X, Karolinum, Prague (2008)
Machač, P., Skarnitzl, R.: Phonetic Analysis of Parasitic Speech Sounds. In: Proceedings of the 19th Czech-German Workshop on Speech Processing, Prague, Czech Rep., pp. 61–68 (2009)
Byrne, W., Doerman, D., Franz, M., Gustman, S., Hajič, J., Oard, D., Picheny, M., Psutka, J., Ramabhadran, B., Soergel, D., Ward, T., Zhu, W.: Automatic Recognition of Spontaneous Speech for Access to Multilingual Oral History Archives. IEEE Transactions on Speech and Audio Processing 4, 420–435 (2004)
Toledano, D., Gómez, L., Grande, L.: Automatic Phonetic Segmentation. IEEE Transactions on Speech and Audio Processing 11(6), 617–625 (2003)
Vaněk, J., Psutka, J.V., Zelinka, J., Pražák, A., Psutka, J.: Discriminative Training of Gender-Dependent Acoustic Models. In: Matoušek, V., Mautner, P. (eds.) TSD 2009. LNCS (LNAI), vol. 5729, pp. 331–338. Springer, Heidelberg (2009)
Matoušek, J.: Automatic Pitch-Synchronous Phonetic Segmentation with Context-Independent HMMs. In: Matoušek, V., Mautner, P. (eds.) TSD 2009. LNCS (LNAI), vol. 5729, pp. 178–185. Springer, Heidelberg (2009)
Schwarz, P., Matějka, P., Černocký, J.: Towards Lower Error Rates In Phoneme Recognition. In: Sojka, P., Kopeček, I., Pala, K. (eds.) TSD 2004. LNCS (LNAI), vol. 3206, pp. 465–472. Springer, Heidelberg (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Matoušek, J. (2010). Automatic Segmentation of Parasitic Sounds in Speech Corpora for TTS Synthesis. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2010. Lecture Notes in Computer Science(), vol 6231. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15760-8_47
Download citation
DOI: https://doi.org/10.1007/978-3-642-15760-8_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15759-2
Online ISBN: 978-3-642-15760-8
eBook Packages: Computer ScienceComputer Science (R0)