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 19, 2026
Muse Glimmer team
October 19, 2026
October 14, 2026
Arturo Loazia-Bonilla
October 14, 2026
October 14, 2026
Daniel Kim
October 14, 2026
October 14, 2026
Paddy Ssentongo
October 14, 2026
