Voice conversion based on feature combination with limited training data
We study four spectral features and compare them. We propose to use cepstral and all-pole features simultaneously in voice conversion. We improve GMM-based and DKPLS methods by feature combination strategy. Our proposed methods are robust to over-fitting and over-smoothing.
voice conversion feature combination gaussian mixture models (gmm) dynamic kernel partial least square regression (dkpls)