A novel approach to remove outliers for parallel voice conversion

Alignment is a key step before learning a mapping function between a source and a target speaker’s spectral features in various state-of-the-art parallel data Voice Conversion (VC) techniques. After alignment, some corresponding pairs are still inconsistent with the rest of the data and are considered outliers. These outliers shift the parameters of the mapping function from their true value and hence, negatively affect the learning of mapping...