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 …
The attacker's perspective on automatic speaker verification: An overview
RK Das, X Tian, T Kinnunen, H Li - 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 …
Unsupervised learning of disentangled and interpretable representations from sequential data
We present a factorized hierarchical variational autoencoder, which learns disentangled and
interpretable representations from sequential data without supervision. Specifically, we …
interpretable representations from sequential data without supervision. Specifically, we …
One-shot voice conversion by separating speaker and content representations with instance normalization
Recently, voice conversion (VC) without parallel data has been successfully adapted to multi-
target scenario in which a single model is trained to convert the input voice to many different …
target scenario in which a single model is trained to convert the input voice to many different …