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 keeping the linguistic …
conversion, we change the speaker identity from one to another, while keeping the linguistic …
An overview of voice conversion systems
SH Mohammadi, A Kain - Speech Communication, 2017 - Elsevier
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 …
Cyclegan-vc: Non-parallel voice conversion using cycle-consistent adversarial networks
We propose a non-parallel voice-conversion (VC) method that can learn a mapping 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 …
Parallel-data-free voice conversion using cycle-consistent adversarial networks
We propose a parallel-data-free voice-conversion (VC) method that can learn a mapping
from source to target speech without relying on parallel data. The proposed method is …
from source to target speech without relying on parallel data. The proposed method is …
Vulnerability of speaker verification systems against voice conversion spoofing attacks: The case of telephone speech
Voice conversion-the methodology of automatically converting one's utterances to sound as
if spoken by another speaker-presents a threat for applications relying on speaker …
if spoken by another speaker-presents a threat for applications relying on speaker …
Voice conversion using partial least squares regression
E Helander, T Virtanen, J Nurminen… - IEEE Transactions on …, 2010 - ieeexplore.ieee.org
Voice conversion can be formulated as finding a mapping function which transforms the
features of the source speaker to those of the target speaker. Gaussian mixture model …
features of the source speaker to those of the target speaker. Gaussian mixture model …
Voice conversion using dynamic kernel partial least squares regression
A drawback of many voice conversion algorithms is that they rely on linear models and/or
require a lot of tuning. In addition, many of them ignore the inherent time-dependency …
require a lot of tuning. In addition, many of them ignore the inherent time-dependency …
Nvc-net: End-to-end adversarial voice conversion
B Nguyen, F Cardinaux - ICASSP 2022-2022 IEEE …, 2022 - ieeexplore.ieee.org
Voice conversion (VC) has gained increasing popularity in many speech synthesis
applications. The idea is to change the voice identity from one speaker into another while …
applications. The idea is to change the voice identity from one speaker into another while …
Synthesizing dysarthric speech using multi-speaker tts for dysarthric speech recognition
M Soleymanpour, MT Johnson… - ICASSP 2022-2022 …, 2022 - ieeexplore.ieee.org
Dysarthria is a motor speech disorder often characterized by reduced speech intelligibility
through slow, uncoordinated control of speech production muscles. Automatic Speech …
through slow, uncoordinated control of speech production muscles. Automatic Speech …
Non-parallel voice conversion using i-vector PLDA: Towards unifying speaker verification and transformation
Text-independent speaker verification (recognizing speakers regardless of content) and non-
parallel voice conversion (transforming voice identities without requiring content-matched …
parallel voice conversion (transforming voice identities without requiring content-matched …