# Bootstrapping non-parallel voice conversion from speaker-adaptive text-to-speech

arXiv: https://arxiv.org/abs/1909.06532 · HTML: https://mlsanity.com/paper/1909.06532/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Sep 2019.

## Built on by (most cited first, 3 of 3)

- [Speech Synthesis with Mixed Emotions](https://mlsanity.com/paper/2208.05890/) (2022)
- [SpeechNet: A Universal Modularized Model for Speech Processing Tasks](https://mlsanity.com/paper/2105.03070/) (2021)
- [Assem-VC: Realistic Voice Conversion by Assembling Modern Speech Synthesis Techniques](https://mlsanity.com/paper/2104.00931/) (2021)

## Abstract (arXiv)

Voice conversion (VC) and text-to-speech (TTS) are two tasks that share a similar objective, generating speech with a target voice. However, they are usually developed independently under vastly different frameworks. In this paper, we propose a methodology to bootstrap a VC system from a pretrained speaker-adaptive TTS model and unify the techniques as well as the interpretations of these two tasks. Moreover by offloading the heavy data demand to the training stage of the TTS model, our VC system can be built using a small amount of target speaker speech data. It also opens up the possibility of using speech in a foreign unseen language to build the system. Our subjective evaluations show that the proposed framework is able to not only achieve competitive performance in the standard intra-language scenario but also adapt and convert using speech utterances in an unseen language.