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Voice Conversion (VC) technique allows to transform the voice of the source speaker so that it is perceived as uttered by the target speaker. In this paper, a novel VC method combining Gaussian Mixture Model (GMM) and Artificial Neural Network is proposed. To overcome the over-smoothing problem of GMM-based mapping method, we propose to convert the basic spectral envelope by GMM method and the residual...
In this paper, we describe a novel conversion method for voice conversion (VC). Artificial Neural Network (ANN) model is employed for performing joint spectrum and pitch conversion between speakers. The conventional method converts spectral parameters and pitch independently. Those separate transformations lead to an unsatisfactory speech quality. The main reason maybe that F0 sequences are usually...
In this paper, we propose to use artificial neural networks (ANN) for voice conversion. We have exploited the mapping abilities of ANN to perform mapping of spectral features of a source speaker to that of a target speaker. A comparative study of voice conversion using ANN and the state-of-the-art Gaussian mixture model (GMM) is conducted. The results of voice conversion evaluated using subjective...
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