相关论文: Egyptian Sign Language Recognition Using CNN and L…

Sign language is a visual language used by the deaf and dumb community to communicate. However, for most recognition methods based on monocular cameras, the recognition accuracy is low and the robustness is poor. Even if the effect is good…

This research paper describes a realtime system for identifying American Sign Language (ASL) movements that employs modern computer vision and machine learning approaches. The suggested method makes use of the Mediapipe library for feature…

Egyptian hieroglyphs are found on numerous ancient Egyptian artifacts, but it is common that they are blurry or even missing due to erosion. Existing efforts to restore blurry hieroglyphs adopt computer vision techniques such as CNNs and…

The automatic interpretation of sign languages is a challenging task, as it requires the usage of high-level vision and high-level motion processing systems for providing accurate image perception. In this paper, we use Convolutional Neural…

Sign languages are the language of hearing-impaired people who use visuals like the hand, facial, and body movements for communication. There are different signs and gestures representing alphabets, words, and phrases. Nowadays…

Sign Language Recognition (SLR) plays a crucial role in bridging the communication gap between the hearing-impaired community and society. This paper introduces SLRNet, a real-time webcam-based ASL recognition system using MediaPipe…

Automatic speech processing systems are employed more and more often in real environments. Although the underlying speech technology is mostly language independent, differences between languages with respect to their structure and grammar…

The hearing-impaired community in India deserves the access to tools that help them communicate, however, there is limited known technology solutions that make use of Indian Sign Language (ISL) at present. Even though there are many ISL…

This research combines MediaPipe and CNNs for the efficient and accurate interpretation of ASL dataset for the real-time detection of sign language. The system presented here captures and processes hands' gestures in real time. the intended…

Recognizing emotions from speech using machine learning has become an active research area due to its importance in building human-centered applications. However, while many studies have been conducted in English, German, and other European…

This study introduces an integrated approach to recognizing Arabic Sign Language (ArSL) using state-of-the-art deep learning models such as MobileNetV3, ResNet50, and EfficientNet-B2. These models are further enhanced by explainable AI…

Existing Sign Language Learning applications focus on the demonstration of the sign in the hope that the student will copy a sign correctly. In these cases, only a teacher can confirm that the sign was completed correctly, by reviewing a…

Over 5% of the world's population (466 million people) has disabling hearing loss. 4 million are children. They can be hard of hearing or deaf. Deaf people mostly have profound hearing loss. Which implies very little or no hearing. Over the…

Sign Language Recognition (SLR) is a fast-growing field that aims to fill the communication gaps between the hearing-impaired and people without hearing loss. Existing solutions for Persian Sign Language (PSL) are limited to word-level…

Sign languages are natural, visual-gestural languages used by Deaf communities worldwide. Over 300 distinct sign languages remain severely low-resource due to limited documentation, sparse datasets, and insufficient computational tools.…

Sign language translation is one of the important issues in communication between deaf and hearing people, as it expresses words through hand, body, and mouth movements. American Sign Language is one of the sign languages used, one of which…

Indonesia ranks fourth globally in the number of deaf cases. Individuals with hearing impairments often find communication challenging, necessitating the use of sign language. However, there are limited public services that offer such…

Recognition of Arabic characters is essential for natural language processing and computer vision fields. The need to recognize and classify the handwritten Arabic letters and characters are essentially required. In this paper, we present…

Sign languages, used by around 70 million Deaf individuals globally, are visual languages that convey visual and contextual information. Current methods in vision-based sign language recognition (SLR) and translation (SLT) struggle with…

Code-switching (CS), defined as the mixing of languages in conversations, has become a worldwide phenomenon. The prevalence of CS has been recently met with a growing demand and interest to build CS ASR systems. In this paper, we present…