RESEARCH

ML APPLICATIONS

TTS Skins: Speaker Conversion via ASR

August 02, 2020

Abstract

We present a fully convolutional wav-to-wav network for converting between speakers' voices, without relying on text. Our network is based on an encoder-decoder architecture, where the encoder is pre-trained for the task of Automatic Speech Recognition, and a multi-speaker waveform decoder is trained to reconstruct the original signal in an autoregressive manner. We train the network on narrated audiobooks, and demonstrate multi-voice TTS in those voices, by converting the voice of a TTS robot.

Download the Paper

AUTHORS

Written by

Adam Polyak

Lior Wolf

Yaniv Taigman

Publisher

INTERSPEECH

Related Publications

October 02, 2026

RESEARCH

Tightness of the Cycle-Based Relaxation for Completed Length-Three Alpha-Cycles

Aykut Arslan

October 02, 2026

October 02, 2026

RESEARCH

On Solvable Evolution Algebras and a Conjecture by García-Martínez and Pérez-Rodríguez

Andres Barei Bueno

October 02, 2026

October 02, 2026

RESEARCH

String Two-Point Function = Height Function on a Curve

Anindya Dey, Gabriel Herczeg, An Huang, Nicolas Jaramillo Torres, Jacob H. Swenberg

October 02, 2026

October 02, 2026

RESEARCH

Semiabelian Groups Need Not Be Monomial

Joseph Phillip Brennan, Milana Golich

October 02, 2026

Help Us Pioneer The Future of AI

We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.