Spoken keyword spotting (KWS) deals with the identification of keywords in audio streams
and has become a fast-growing technology thanks to the paradigm shift introduced by deep …

Despite the rapid progress of automatic speech recognition (ASR) technologies in the past
few decades, recognition of disordered speech remains a highly challenging task to date …

Visual speech recognition (VSR) aims to recognize the content of speech based on lip
movements, without relying on the audio stream. Advances in deep learning and the …

In this work, we present a hybrid CTC/Attention model based on a ResNet-18 and
Convolution-augmented transformer (Conformer), that can be trained in an end-to-end …

Generating speech-consistent body and gesture movements is a long-standing problem in
virtual avatar creation. Previous studies often synthesize pose movement in a holistic …

Audio-visual speech recognition has received a lot of attention due to its robustness against
acoustic noise. Recently, the performance of automatic, visual, and audio-visual speech …

The goal of this paper is to learn strong lip reading models that can recognise speech in
silent videos. Most prior works deal with the open-set visual speech recognition problem by …

Co-speech gesture is crucial for human-machine interaction and digital entertainment. While
previous works mostly map speech audio to human skeletons (eg, 2D keypoints), directly …

This paper deals with Audio-Visual Speech Recognition (AVSR) under multimodal input
corruption situation where audio inputs and visual inputs are both corrupted, which is not …

Abstract End-to-end Automatic Speech Recognition (ASR) systems based on neural
networks have seen large improvements in recent years. The availability of large scale hand …