Voice morphing is a technique to modify a source speaker’s speech to sound as if it was spoken by some designated target speaker. The Gaussian mixture model (GMM) based transformations combined with full-band extracted feature parameters have been commonly studied. However

these methods often introduce problems such as artifacts and discontinuities. In order to resolve the problem mentioned above

state-space model (SSM) is first used to describe the relationship between the source speech and the target speech in the spectral domain. Then Discrete Wavelet Transform (DWT) is applied to decompose speech signals into sub-bands in order to improve the quality of the converted speech. Finally

experiments using both objective and subjective measurements are conducted to validate the effectiveness of the proposed method..