Abstract
In this paper we will present the method we have used to collect a large database using live recording of a radio transmission and of an announcer. Our selection method uses phonetic and prosodic context information and frequency domain measurements in a search algorithm based on minimising two cost functions: the concatenation cost between adjacent speech units and the distance between the selected unit and a previously calculated target segment. For each basic unit, on average, we have collected around 100 similar units in different phonetic and prosodic contexts. To segment the basic units, we have used our highly accurate speech recognition system described in [1]. This collection of units has been used in our TTS system giving marked improvement in naturalness. With this new system, we hope to help people with disabilities that need to listen or speak using artificial speech.
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References
SRS-2000: A Speech Recognition System, Internal Report, Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, 1999.
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Gómez-Mena, J., Cardo, M., Madrid, J.L., Prades, C. (2000). Database Processing for Spanish Text-to-Speech Synthesis. In: Sojka, P., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2000. Lecture Notes in Computer Science(), vol 1902. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45323-7_42
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DOI: https://doi.org/10.1007/3-540-45323-7_42
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