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Powered by AI, QuickPic creates topic-specific displays automatically from photographs to support communication and language learning for non-speaking individuals, their families, and speech-language pathologists (SLPs)

QuickPic AAC

by Mauricio Fontana de Vargas

What is it about?

Powered by AI, QuickPic creates topic-specific displays automatically from photographs to support communication and language learning for non-speaking individuals, their families, and speech-language pathologists (SLPs).

App Details

Version
1.0.2
Rating
(2)
Size
522Mb
Genre
Education Medical
Last updated
November 8, 2023
Release date
September 1, 2023
More info

App Screenshots

App Store Description

Powered by AI, QuickPic creates topic-specific displays automatically from photographs to support communication and language learning for non-speaking individuals, their families, and speech-language pathologists (SLPs).

Choose a photograph, and in a few seconds QuickPic will create a topic-specific display containing vocabulary symbols (pictograms) related to the input photograph!

Topic-specific displays are a single page containing all relevant vocabulary to discuss a certain topic or activity. Users can then select vocabulary to create sentences using synthesized speech.

QuickPic is fully customizable:

~> You can edit the topic display created to add or remove words, or select a better symbol for a specific word.
~> You can change the size of all elements in the interface.
~> You can choose the complexity of vocabulary generated automatically.
~> You can program familiar people to enable QuickPic to automatically recognize them when creating new boards.

QuickPic was designed by a team of experts (PhDs and CCC-SLPs) in the field of speech-language therapy and human-computer interaction (HCI) using user-centered design methodologies, which involved the participation of end-users in the process.


*** Development of this application was partly supported by the App Factory to Support Health and Function of People with Disabilities funded by a grant from the National Institute on Disability, Independent Living and Rehabilitation Research (NIDILRR) in the U.S. Department of Health and Human Services to the Shepherd Center (Grant # 90DPHF0004) ***




Created by Mauricio Fontana de Vargas (PhD), Howard Shane (PhD), and Christina Yu (CCC-SLP).

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