American Sign Language Recognition
In this article, a simple and efficient vision-based approach for American Sign Language (ASL) alphabets recognition has been discussed to recognize both static and dynamic gestures. Mediapipe introduced by Google had been used to get hand landmarks and a custom dataset has been created and used for the experimental study. American Alphabet Sign Language Recognition System The most ordinary form of communication relies on alphabetic expression through speech, writing, or sign language.
Abstract Our paper presents a two-pronged ablation study for sign language recognition for American Sign Language (ASL) characters on two datasets. Experimentation re-vealed that hyperparameter tuning, data augmentation, and hand landmark detection can help improve accuracy. The fi-nal model achieved a test accuracy of 96.42%.
Two-Stream Mixed Convolutional Neural Network for American Sign ...
Future work includes running the model for a greater number of. A study is the first-of-its-kind to recognize American Sign Language (ASL) alphabet gestures using computer vision. Researchers developed a custom dataset of 29,820 static images of ASL hand.
The American Sign Language Recognition Dataset is a pivotal resource for research in visual. American Sign Language (ASL) recognition aims to recognize hand gestures, and it is a crucial solution to communicating between the deaf community and hearing people. However, existing sign language recognition algorithms still have some drawbacks, such as difficulty recognizing hand movements and low recognition accuracy for most sign language recognition.
American Sign Language Recognition Using Leap Motion Controller with ...
A Modified Convolutional Neural. In order to bridge this gap and connect deaf- mute with the rest of the world, with the help of deep learning, Sign Language Recognition (SLR) model has been introduced to revolutionize the way sign language is integrated into daily life, enhance communication, accessibility, and inclusively. ASL recognition is divided into two types, namely, recognitions of static and dynamic gestures.
This paper is focused on static fingerspelling in ASL language. It is a very significant portion of sign languages recognition because it is used in many situations such as brands, addresses, names, and so on. The static gestures.
American Sign Language Hand Gesture Recognition | by Rawini Dias ...
"By improving American Sign Language recognition, this work contributes to creating tools that can enhance communication for the deaf and hard-of-hearing community," says Stella Batalama, PhD, dean, FAU College of Engineering and Computer Science. "The model's ability to reliably interpret gestures opens the door to more inclusive solutions that support accessibility, making daily. American Sign Language (ASL) is one of the most widely used sign languages, consisting of distinct hand gestures that represent letters, words, and phrases.
However, existing ASL recognition systems often struggle with real-time performance, accuracy, and robustness across diverse environments.
