An overview of voice conversion and its challenges: From statistical modeling to deep learning
Speaker identity is one of the important characteristics of human speech. In voice
conversion, we change the speaker identity from one to another, while kee** the linguistic …
conversion, we change the speaker identity from one to another, while kee** the linguistic …
An overview of voice conversion systems
Voice transformation (VT) aims to change one or more aspects of a speech signal while
preserving linguistic information. A subset of VT, Voice conversion (VC) specifically aims to …
preserving linguistic information. A subset of VT, Voice conversion (VC) specifically aims to …
Neural analysis and synthesis: Reconstructing speech from self-supervised representations
We present a neural analysis and synthesis (NANSY) framework that can manipulate the
voice, pitch, and speed of an arbitrary speech signal. Most of the previous works have …
voice, pitch, and speed of an arbitrary speech signal. Most of the previous works have …
Autovc: Zero-shot voice style transfer with only autoencoder loss
Despite the progress in voice conversion, many-to-many voice conversion trained on non-
parallel data, as well as zero-shot voice conversion, remains under-explored. Deep style …
parallel data, as well as zero-shot voice conversion, remains under-explored. Deep style …
Voice conversion challenge 2020: Intra-lingual semi-parallel and cross-lingual voice conversion
Y Zhao, WC Huang, X Tian, J Yamagishi… - ar** from
source to target speech without relying on parallel data. The proposed method is particularly …
source to target speech without relying on parallel data. The proposed method is particularly …