In the recent past, research in the field of automatic sign language recognition using
machine learning methods have demonstrated remarkable success and made momentous …

Sign language is a form of visual communication employing hand gestures, body
movements, and facial expressions. The growing prevalence of hearing impairment has …

Sign language facilitates communication between hearing impaired peoples and the rest of
the society. A number of sign language recognition (SLR) systems have been developed by …

This chapter covers the key aspects of sign-language recognition (SLR), starting with a brief
introduction to the motivations and requirements, followed by a précis of sign linguistics and …

This paper discusses sign language recognition using linguistic sub-units. It presents three
types of sub-units for consideration; those learnt from appearance data as well as those …

Automatic sign language recognition is a research area that encompasses human-computer
interaction, computer vision and machine learning. Robust automatic recognition of sign …

This paper presents a novel, discriminative, multi-class classifier based on Sequential
Pattern Trees. It is efficient to learn, compared to other Sequential Pattern methods, and …

We introduce a new computational phonetic modeling framework for sign language (SL)
recognition. This is based on dynamic–static statistical subunits and provides sequentiality …

We explore novel directions for incorporating phonetic transcriptions into sub-unit based
statistical models for sign language recognition. First, we employ a new symbolic processing …

Automatic sign language recognition is an important topic within the areas of human-
computer interaction and machine learning. On the one hand, it poses a complex challenge …