Abstract
Unit selection is a very popular approach to speech synthesis. It is known for its ability to produce nearly natural-sounding synthetic speech, but, at the same time, also for its need for very large speech corpora. In addition, unit selection is also known to be very sensitive to the quality of the source speech corpus the speech is synthesised from and its textual, phonetic and prosodic annotations and indexation. Given the enormous size of current speech corpora, manual annotation of the corpora is a lengthy process. Despite this fact, human annotators do make errors. In this paper, the impact of annotation errors on the quality of unit-selection-based synthetic speech is analysed. Firstly, an analysis and categorisation of annotation errors is presented. Then, a speech synthesis experiment, in which the same utterances were synthesised by unit-selection systems with and without annotation errors, is described. Results of the experiment and the options for fixing the annotation errors are discussed as well.
Support for this work was provided by the TA CR, project No. TA01030476, and by the European Regional Development Fund, project “New Technologies for Information Society”, European Centre of Excellence, ED1.1.00/02.0090.
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Matoušek, J., Tihelka, D., Šmídl, L. (2012). On the Impact of Annotation Errors on Unit-Selection Speech Synthesis. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2012. Lecture Notes in Computer Science(), vol 7499. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32790-2_55
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DOI: https://doi.org/10.1007/978-3-642-32790-2_55
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