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 …

Easy access to audio-visual content on social media, combined with the availability of
modern tools such as Tensorflow or Keras, and open-source trained models, along with …

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 …

The voice conversion challenge is a bi-annual scientific event held to compare and
understand different voice conversion (VC) systems built on a common dataset. In 2020, we …

In this paper, we first provide a review of the state-of-the-art emotional voice conversion
research, and the existing emotional speech databases. We then motivate the development …

The remarkable success of transformers in the field of natural language processing has
sparked the interest of the speech-processing community, leading to an exploration of their …

We present the latest iteration of the voice conversion challenge (VCC) series, a bi-annual
scientific event aiming to compare and understand different voice conversion (VC) systems …

Current AI-assisted protein design mainly utilizes protein sequential and structural
information. Meanwhile, there exists tremendous knowledge curated by humans in the text …

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 …

Human intelligence is multimodal; we integrate visual, linguistic, and acoustic signals to
maintain a holistic worldview. Most current pretraining methods, however, are limited to one …