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 …

Voice style transfer, also called voice conversion, seeks to modify one speaker's voice to
generate speech as if it came from another (target) speaker. Previous works have made …

Non-parallel many-to-many voice conversion remains an interesting but challenging speech
processing task. Many style-transfer-inspired methods such as generative adversarial …

Although recent advances in voice conversion have shown significant improvement, there
still remains a gap between the converted voice and target voice. A key factor that maintains …

We present an unsupervised non-parallel many-to-many voice conversion (VC) method
using a generative adversarial network (GAN) called StarGAN v2. Using a combination of …

Traditional voice conversion methods rely on parallel recordings of multiple speakers
pronouncing the same sentences. For real-world applications however, parallel data is …

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 …

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 …

Singing voice conversion (SVC) is a task to convert the source singer's voice to sound like
that of the target singer, without changing the lyrical content. So far, most of the voice …

We present a novel voice conversion (VC) framework by learning from a text-to-speech
(TTS) synthesis system, that is called TTS-VC transfer learning or TTL-VC for short. We first …