Generative AI for Sign Language Recognition and Translation - (Computing and Networks) by Elakkiya Rajasekar (Hardcover)
About this item
Highlights
- Sign languages differ from written languages, having their own grammar and syntax.
- Author(s): Elakkiya Rajasekar
- 350 Pages
- Computers + Internet, Intelligence (AI) & Semantics
- Series Name: Computing and Networks
Description
About the Book
In this book, the author takes a multidisciplinary approach combining insights from AI, linguistics, speech recognition and sign language studies to provide a holistic understanding of Generative AI for sign language translation and present innovative solutions to promote effective communication, accessibility and inclusivity.
Book Synopsis
Sign languages differ from written languages, having their own grammar and syntax. A written language is two-dimensional whereas a sign language encompasses a three-dimensional communication system that involves not only hand gestures but also facial expressions, body movements, and spatial relationships. These non-manual components are crucial in conveying grammatical features, nuances, and emotional tones within sign language communication. A single sign can therefore have several meanings.
Generative AI-generated sign language solutions use speech recognition and artificial intelligence (AI) to interpret spoken or written language into sign languages, and can translate written documents, sentences on websites, video subtitles and even real-time speech. They can also translate sign languages into text or voice to facilitate the communication for people who do not know sign languages.
This book aims to delve into the intricate nuances of sign languages and explores how generative AI models can effectively capture and interpret these linguistic elements. By harnessing advanced speech recognition algorithms and machine learning techniques, generative AI models can learn the complex grammar and syntax of sign languages, including the subtle variations in handshapes, movements, and facial expressions. Through comprehensive training on diverse sign language datasets, these models can acquire the proficiency to generate accurate and contextually relevant sign language interpretations of spoken or written content.
In this book, the author takes a multidisciplinary approach that combines insights from artificial intelligence, linguistics, speech recognition and sign language studies to provide a holistic understanding of the role of generative AI in sign language translation. Additionally, the book features case studies and practical applications that demonstrate the real-world impact and potential of AI-generated sign language solutions in promoting effective communication, accessibility and inclusivity.
The cross-disciplinary nature of this book is suited to a range of audiences and interests, including ICT researchers, scientists and engineers in industry and academia, and technology professionals in the fields of computing, AI, mobile computing, networking, data science, speech recognition, HCI and sensing, with a focus on sign language recognition and translation. Linguists with an interest in sign language recognition and translation will also find a useful resource in this book, as will developers and designers of AI-based sign language recognition and translation platforms, devices and apps.