The advancements in neural networks and the on-demand need for accurate and near real-
time Speech Emotion Recognition (SER) in human–computer interactions make it …

Nowadays emotion recognition from speech (SER) is a demanding research area for
researchers because of its wide real-life applications. There are many challenges for SER …

In this work, we tackle the challenge of enhancing the realism and expressiveness in talking
head video generation by focusing on the dynamic and nuanced relationship between audio …

As 3D facial avatars become more widely used for communication, it is critical that they
faithfully convey emotion. Unfortunately, the best recent methods that regress parametric 3D …

Audio-visual learning helps to comprehensively understand the world, by integrating
different senses. Accordingly, multiple input modalities are expected to boost model …

Talking face generation has historically struggled to produce head movements and natural
facial expressions without guidance from additional reference videos. Recent developments …

Although significant progress has been made to audio-driven talking face generation,
existing methods either neglect facial emotion or cannot be applied to arbitrary subjects. In …

We summarize the results of a host of efforts using giant automatic speech recognition (ASR)
models pre-trained using large, diverse unlabeled datasets containing approximately a …

The synthesis of natural emotional reactions is an essential criterion in vivid talking-face
video generation. This criterion is nevertheless seldom taken into consideration in previous …

The RAVDESS is a validated multimodal database of emotional speech and song. The
database is gender balanced consisting of 24 professional actors, vocalizing lexically …