Vision-Based American Sign Language Classification Approach via Deep Learning
This addresses communication challenges for hearing-impaired communities, but it appears incremental as it applies existing deep learning methods to ASL classification.
The paper tackled the problem of communication barriers for hearing-impaired individuals by proposing a deep learning model to classify American Sign Language letters, but no concrete results or numbers are provided.
Hearing-impaired is the disability of partial or total hearing loss that causes a significant problem for communication with other people in society. American Sign Language (ASL) is one of the sign languages that most commonly used language used by Hearing impaired communities to communicate with each other. In this paper, we proposed a simple deep learning model that aims to classify the American Sign Language letters as a step in a path for removing communication barriers that are related to disabilities.