Sight and hearing are two senses that play a vital role in human communication and scene
understanding. To mimic human perception ability, audio-visual learning, aimed at …

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

Audio-visual speech recognition (AVSR) is one of the most promising solutions for reliable
speech recognition, particularly when audio is corrupted by noise. Additional visual …

Several end-to-end deep learning approaches have been recently presented which extract
either audio or visual features from the input images or audio signals and perform speech …

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

Lipreading has witnessed a lot of progress due to the resurgence of neural networks. Recent
works have placed emphasis on aspects such as improving performance by finding the …

Recent works in speech recognition rely either on connectionist temporal classification
(CTC) or sequence-to-sequence models for character-level recognition. CTC assumes …

In this work, we present the Densely Connected Temporal Convolutional Network (DC-TCN)
for lip-reading of isolated words. Although Temporal Convolutional Networks (TCN) have …

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 …