Clizia Giorgia Manganaro
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Clizia Giorgia Manganaro has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Alessio Palma
Sapienza University of Rome
1 shared publication - Chiara Giacanelli
Computer Science, Sapienza University of Rome, Italy
1 shared publication - Davide Santoro
Computer Science, Sapienza University of Rome, Italy
1 shared publication - Maria De Marsico
Department of Computer Science, Sapienza University of Rome, Rome, Italy
1 shared publication
Latest Publications
- Open Access
- 3 June 2024
- Published by Association for Computing Machinery (ACM)
- p. 1-5
VQAsk: a multimodal Android GPT-based application to help blind users visualize pictures
VQAsk is an Android application that helps visually impaired users to get information about images framed by their smartphones. It enables to interact with one’s photographs or the surrounding visual environment through a question-and-answer interface integrating three modalities: speech interaction, haptic feedback that facilitates navigation and interaction, and sight. VQAsk is primarily designed to help visually impaired users mentally visualize what they cannot see, but it can also accommodate users with varying levels of visual ability. To this aim, it embeds advanced NLP and Computer Vision techniques to answer all user questions about the image on the cell screen. Image processing is enhanced by background removal through advanced segmentation models that identify important image elements. The outcomes of a testing phase confirmed the importance of this project as a first attempt at using AI-supported multimodality to enhance visually impaired users’ experience.
- 3 June 2024
- Published by Association for Computing Machinery (ACM)
- p. 1-5
Open AccessVQAsk: a multimodal Android GPT-based application to help blind users visualize pictures
VQAsk is an Android application that helps visually impaired users to get information about images framed by their smartphones. It enables to interact with one’s photographs or the surrounding visual environment through a question-and-answer interface integrating three modalities: speech interaction, haptic feedback that facilitates navigation and interaction, and sight. VQAsk is primarily designed to help visually impaired users mentally visualize what they cannot see, but it can also accommodate users with varying levels of visual ability. To this aim, it embeds advanced NLP and Computer Vision techniques to answer all user questions about the image on the cell screen. Image processing is enhanced by background removal through advanced segmentation models that identify important image elements. The outcomes of a testing phase confirmed the importance of this project as a first attempt at using AI-supported multimodality to enhance visually impaired users’ experience.