The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …

Voice conversion is a process where the essence of a speaker's identity is seamlessly
transferred to another speaker, all while preserving the content of their speech. This usage is …

Voice conversion is a common speech synthesis task which can be solved in different ways
depending on a particular real-world scenario. The most challenging one often referred to as …

Voice conversion (VC) can be achieved by first extracting source content information and
target speaker information, and then reconstructing waveform with these information …

Emotional voice conversion (EVC) seeks to convert the emotional state of an utterance while
preserving the linguistic content and speaker identity. In EVC, emotions are usually treated …

Language models (LMs) have demonstrated the capability to handle a variety of generative
tasks. This paper presents the UniAudio system, which, unlike prior task-specific …

Various applications of voice synthesis have been developed independently despite the fact
that they generate" voice" as output in common. In addition, the majority of voice synthesis …

Any-to-any voice conversion problem aims to convert voices for source and target speakers,
which are out of the training data. Previous works wildly utilize the disentangle-based …

Non-parallel data voice conversion (VC) have achieved considerable breakthroughs
recently through introducing bottleneck features (BNFs) extracted by the automatic speech …

Any-to-any voice conversion aims to transform source speech into a target voice with just a
few examples of the target speaker as a reference. Recent methods produce convincing …