August 02, 2020
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.
October 02, 2026
Aykut Arslan
October 02, 2026
October 02, 2026
Andres Barei Bueno
October 02, 2026
October 02, 2026
Anindya Dey, Gabriel Herczeg, An Huang, Nicolas Jaramillo Torres, Jacob H. Swenberg
October 02, 2026
October 02, 2026
Joseph Phillip Brennan, Milana Golich
October 02, 2026
