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 …

We investigated the training of a shared model for both text-to-speech (TTS) and voice
conversion (VC) tasks. We propose using an extended model architecture of Tacotron, that …

Thanks to the growing availability of spoofing databases and rapid advances in using them,
systems for detecting voice spoofing attacks are becoming more and more capable, and …

Deep-learning methods, such as convolutional neural networks (CNNs), have been
successfully applied to seismic impedance inversion in recent years. Compared with …

Dysarthria is a motor speech disorder often characterized by reduced speech intelligibility
through slow, uncoordinated control of speech production muscles. Automatic Speech …

Voice conversion (VC) techniques can be abused by malicious parties to transform their
audios to sound like a target speaker, making it hard for a human being or a speaker …

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 …

This paper introduces a novel voice conversion (VC) model, guided by text instructions such
as “articulate slowly with a deep tone “or “speak in a cheerful boyish voice”. Unlike …

Speaker anonymization is a method of protecting voice privacy by concealing individual
speaker characteristics while preserving linguistic information. The VoicePrivacy Challenge …

An effective approach to non-parallel voice conversion (VC) is to utilize deep neural
networks (DNNs), specifically variational auto encoders (VAEs), to model the latent structure …