Voice conversion based on RBF neural network

Recently, voice conversion has becoming the research hotspot, because of its widely application areas. However, the voice conversion technology is still immature. By the researching of existing voice conversion models, the voice conversion system based on the RBF neutral network was designed, and the system simulation was implemented. During conversion, the unvoiced speech was excluded and the voiced speech was reserved. The LPC was the extracted from the source and target speech, then convert the LPC to LSP. The LPS was trained by RBF neural network after time-aligned. Obtained mapping function was used to convert the source LSP to target LSP, and synthesis the speech. Finally, the converted speech evaluated by ABX and MOS to test the tendency and quality of the speech.