Voice conversion for unknown speakers

Voice conversion is a technique for modifying a source speaker’s speech to sound as if it was spoken by a target speaker. The conventional solutions to this problem are based on training and applying conversion functions which require a substantial amount of training data from both the source and the target speaker. In this paper, we present a voice conversion technique that requires no preexisting training data from the source speaker. This new approach uses a speech recognizer to index the target training data so that each unknown source frame can be used to retrieve similar frames from the target database. The retrieved frames are then used to estimate conversion functions in a similar way to conventional methods. The paper presents both objective and subjective evaluations of the method. It also explores a number of variants including the contrast between using single and multiple transforms, and between the cases where the content of the source speech is known or unknown. The overall conclusion of the paper is that the method presented can result in identification of the target speaker with as little as a single sentence of source data to transform, however, knowledge of the source orthography is needed to attain a close similarity.