Zero-shot Cross-lingual Voice Transfer for TTS
Authors: name: Fadi Biadsy, name: Youzheng Chen, name: Isaac Elias, name: Kyle Kastner, name: Gary Wang, name: Andrew Rosenberg, name: Bhuvana Ramabhadran

In this paper, we introduce a zero-shot Voice Transfer (VT) module that can
be seamlessly integrated into a multi-lingual Text-to-speech (TTS) system to
transfer an individual's voice across languages. Our proposed VT module
comprises a speaker-encoder that processes reference speech, a bottleneck
layer, and residual adapters, connected to preexisting TTS layers. We compare
the performance of various configurations of these components and report Mean
Opinion Score (MOS) and Speaker Similarity across languages. Using a single
English reference speech per speaker, we achieve an average voice transfer
similarity score of 73% across nine target languages. Vocal characteristics
contribute significantly to the construction and perception of individual
identity. The loss of one's voice, due to physical or neurological conditions,
can lead to a profound sense of loss, impacting one's core identity. As a case
study, we demonstrate that our approach can not only transfer typical speech
but also restore the voices of individuals with dysarthria, even when only
atypical speech samples are available - a valuable utility for those who have
never had typical speech or banked their voice. Cross-lingual typical audio
samples, plus videos demonstrating voice restoration for dysarthric speakers
are available here
(google.github.io/tacotron/publications/zero_shot_voice_transfer).