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

TL;DR
This paper presents a zero-shot cross-lingual voice transfer module integrated into TTS systems, enabling voice cloning across languages with minimal reference data, and demonstrating utility for dysarthric voice restoration.
Contribution
Introduces a novel zero-shot voice transfer module for multi-lingual TTS that works with a single reference speech and can restore voices of individuals with speech impairments.
Findings
Achieved 73% voice transfer similarity across nine languages.
The module effectively transfers voice identity with minimal reference data.
Restores voices of dysarthric speakers using atypical speech samples.
Abstract
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…
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Taxonomy
TopicsSpeech Recognition and Synthesis · Speech and Audio Processing
