AI at the Edge for Sign Language Learning Support

Battistoni, Pietro; Gregorio, Marianna Di; Sebillo, Monica; Vitiello, Giuliana

doi:10.1109/hcc46620.2019.00011

Cited by 14 publications

(6 citation statements)

References 19 publications

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“…Kim et al [13] proposed a novel sign language recognition method, which employs an object detection network for a region of interest segmentation to preprocess the input data. Battistoni et al [2] described a method for ASL alphabet recognition based on CNNs, which allows for monitoring the users' learning progress. Jiang et al [12] proposed a novel fingerspelling identification method for Chinese Sign Language via AlexNet-based transfer learning and evaluated four different methods of transfer learning.…”

Section: Sign Language Detection and Recognitionmentioning

confidence: 99%

User-Defined Hand Gesture Interface to Improve User Experience of Learning American Sign Language

Wang

Ivrissimtzis

et al. 2023

Lecture Notes in Computer Science

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Sign language can make possible effective communication between hearing and deaf-mute people. Despite years of extensive pedagogical research, learning sign language remains a formidable task, with the majority of the current systems relying extensively on online learning resources, presuming that users would regularly access them; yet, this approach can feel monotonous and repetitious. Recently, gamification has been proposed as a solution to the problem, however, the research focus is on game design, rather than user experience design. In this work, we present a system for user-defined interaction for learning static American Sign Language (ASL), supporting gesture recognition for user experience design, and enabling users to actively learn through involvement with user-defined gestures, rather than just passively absorbing knowledge. Early findings from a questionnaire-based survey show that users are more motivated to learn static ASL through user-defined interactions.

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Section: Sign Language Detection and Recognitionmentioning

confidence: 99%

User-Defined Hand Gesture Interface to Improve User Experience of Learning American Sign Language

Wang

Ivrissimtzis

et al. 2023

Lecture Notes in Computer Science

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“…Inspired by the previous research about the sign languages interpretation through AI, Refs. [ 14 , 15 , 16 ], the proposed TactCube device would be used in future work to create manipulation-generated tactile signs that could be interpreted by AI.…”

Section: The Tactcube Conceptsmentioning

confidence: 99%

TactCube: An Intelligent Device to ‘converse’ with Smart Environments

Battistoni

Gregorio

Romano

et al. 2022

Sensors

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Ambient Intelligence is a vision of daily life in which intelligent devices interact with humans to make their lives easier, and the technology is invisible. Artificial Intelligence (AI) governs this smart environment and must interact with humans to best meet their needs and demands. Although voice assistants are very popular and efficient as conversational AI, under some conditions they cannot be used. Therefore, this work proposed a complementary tactile and tangible interface to converse with AI, creating new Tactile Signs. A prototype of TactCube, a wireless cube-shaped device that can interact with AI using only the tactile sense, is presented. The hypothesis is that TactCube can be manipulated with one hand and generate a sequence of numbers that can be interpreted as a new tactile language by a neural network solution. The paper describes the initial research made to define how these sequences can be generated and demonstrates how TactCube is able to do it.

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“…Since in [1] there was a high acceptance obtained by mobile applications within the deaf community as a valid means of communication, the aim was to offer a mobile solution for learning. Giving rise to the idea of a Fog-Computing architecture, which could provide additional computing resources to end-user devices connected locally [11]. In addition, the research was aimed at providing sign language learners with a beneficial interactive experience.…”

Section: Conducted Researchmentioning

confidence: 99%

Accessible Applications - Study and Design of User Interfaces to Support Users with Disabilities

Gregorio

2021

Proceedings of the 2021 International Conference on Multimodal Interaction

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Mobile applications are currently one of the primary means enabling any kind of social and human interaction. Being so pervasive, these applications should be made usable for all users: accessibility collects the guidelines that developers should follow to include features allowing users with disabilities (e.g., visual impairments) to better interact with an application. The external quality and, particularly, the usability of these apps influences the application acceptance and usage patterns. For this reason, developers are increasing their attention to the problem of accessibility, which is the branch of computer-human interaction that defines the guidelines to make an application usable by all users. This article describes the purpose and progress of the author's doctoral studies on user interaction, usability, and motivational questions related to the accessibility of mobile applications. CCS CONCEPTS• Human-centered computing → Accessibility; Empirical studies in accessibility.

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AI at the Edge for Sign Language Learning Support

Cited by 14 publications

References 19 publications

User-Defined Hand Gesture Interface to Improve User Experience of Learning American Sign Language

User-Defined Hand Gesture Interface to Improve User Experience of Learning American Sign Language

TactCube: An Intelligent Device to ‘converse’ with Smart Environments

Accessible Applications - Study and Design of User Interfaces to Support Users with Disabilities

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