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TTS Skins: Speaker Conversion via ASR

Adam Polyak, Lior Wolf, Yaniv Taigman

Year
2019
Access
Open access

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.

Keywords

cs.SDcs.LGstat.ML

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