Phonetic anchor based state mapping for text-independent voice conversion

This paper describes a novel method for text-independent voice conversion using improved state mapping. HMM is used for representing the phonetic structure of training speech. Centroids of the common phonemes between source and target speech are utilized as phonetic anchors while establishing a mapping between acoustic spaces of source and target speakers. These phonetic anchors and weighted linear transform are used for creating a continuous parametric mapping from source to target speech parameters. The proposed technique is applicable to both intra-lingual and cross-lingual voice conversion. Experimental results show that state mapping is improved using proposed technique.