User authentication systems (in short authentication systems) have wide utilization in our
daily life. Unfortunately, existing authentication systems are prone to various attacks while …

In the last few years, there has been an increasing interest in develo** systems for
Automatic Lip-Reading (ALR). Similarly to other computer vision applications, methods …

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

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 …

We propose an end-to-end deep learning architecture for word-level visual speech
recognition. The system is a combination of spatiotemporal convolutional, residual and …

Deep networks have been successfully applied to unsupervised feature learning for single
modalities (eg, text, images or audio). In this work, we propose a novel application of deep …

Real data are often with multiple modalities or comingfrom multiple channels, while multi-
view clusteringprovides a natural formulation for generating clustersfrom such data …

Automatic speech recognition (ASR) is the major human–machine interface in many
intelligent systems, such as intelligent homes, autonomous driving, and servant robots …

This work presents a scalable solution to open-vocabulary visual speech recognition. To
achieve this, we constructed the largest existing visual speech recognition dataset …

In this paper, we review the major approaches to multimodal human–computer interaction,
giving an overview of the field from a computer vision perspective. In particular, we focus on …