Abstract
In this study, we introduce the method of reconstructing more natural synthetic voice by using radial basis function network (RBF) that is one of neural network that is suitable for function approximation problems and following and synthesizing vocal fluctuations. In the synthetic simulation of RBF, we have set the Gaussian function based on parameters and tried to reconstruct the vocal fluctuations. With respect to parameter estimation, we have adopted to nonlinear least-squares method for making much account of the nonlinearity of human voice. When we have reproduced the synthesized speech, we have tried to reconstruct the nonlinear fluctuations of amplitude by adding normal random number. We have made a comparison the real voice and the synthetic voice obtained from simulation. As a consequence, we have found that it was possible to synthesize the vocal fluctuations for a short time.
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Naniwa, Y., Kondo, T., Kamiyama, K., Kamata, H. (2012). Study on the Artificial Synthesis of Human Voice Using Radial Basis Function Networks. In: Kim, JH., Lee, K., Tanaka, S., Park, SH. (eds) Advanced Methods, Techniques, and Applications in Modeling and Simulation. Proceedings in Information and Communications Technology, vol 4. Springer, Tokyo. https://doi.org/10.1007/978-4-431-54216-2_32
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DOI: https://doi.org/10.1007/978-4-431-54216-2_32
Publisher Name: Springer, Tokyo
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