Can voice conversion be used to reduce non-native accents?

Voice-conversion (VC) techniques aim to transform utterances from a source speaker to sound as if a target speaker had produced them. For this reason, VC is generally ill-suited for accent-conversion (AC) purposes, where the goal is to capture the regional accent of the source while preserving the voice quality of the target. In this paper, we propose a modification of the conventional training process for VC that allows it to perform as an AC transform. Namely, we pair source and target vectors based not on their ordering within a parallel corpus, as is commonly done in VC, but based on their linguistic similarity. We validate the approach on a corpus containing native-accented and Spanish-accented utterances, and compare it against conventional VC through a series of listening tests. We also analyze whether phonological differences between the two languages (Spanish and American English) help predict the performance of the two methods.