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 …

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 …

Visual speech information plays an important role in automatic speech recognition (ASR)
especially when audio is corrupted or even inaccessible. Despite the success of audio …

Abstract We propose a Deep Boltzmann Machine for learning a generative model of
multimodal data. We show how to use the model to extract a meaningful representation of …

In this paper, we present methods in deep multimodal learning for fusing speech and visual
modalities for Audio-Visual Automatic Speech Recognition (AV-ASR). First, we study an …

Visual speech constitutes a large part of our nonrigid facial motion and contains important
information that allows machines to interact with human users, for instance, through …

Automatic lip-reading (ALR) aims to recognize words using visual information from the
speaker's lip movements. In this work, we introduce a novel type of sensing device, event …

A survey on automated lip-reading approaches is presented in this paper with the main
focus being on deep learning related methodologies which have proven to be more fruitful …

In this paper, a neural network-based lip reading system is proposed. The system is lexicon-
free and uses purely visual cues. With only a limited number of visemes as classes to …

Human speech perception is intrinsically a multi-modal task since speech production
requires the speaker to move the lips, producing visual cues in addition to auditory …