Unsupervised Polyglot Text To Speech

May 11, 2019

Abstract

We present a TTS neural network that is able to produce speech in multiple languages. The proposed network is able to transfer a voice, which was presented as a sample in a source language, into one of several target languages. Training is done without using matching or parallel data, i.e., without samples of the same speaker in multiple languages, making the method much more applicable. The conversion is based on learning a polyglot network that has multiple per-language sub-networks and adding loss terms that preserve the speaker’s identity in multiple languages. We evaluate the proposed polyglot neural network for three languages with a total of more than 400 speakers and demonstrate convincing conversion capabilities.

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AUTHORS

Written by

Eliya Nachmani

Lior Wolf

Publisher

International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Research Topics

NLP

Speech & Audio

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