SlideWiki | Multilingual Symbolic Support for Low Levels of Literacy on the Web

Multilingual Symbolic Support for Low Levels of Literacy on the Web

E.A. Draffan, Mike Wald, Chaohai Ding and Russell Newman

WebSci 2020

The Problem

Content on the web can be:

Complex ≈16% over 60s have mild cognitive impairment (WHO)
Hard to simplify
Incomprehensible for those with poor literacy levels.

2

What are low levels of literacy?

“750 million adults – two-thirds of whom are women – still lack basic reading and writing skills”. The benchmark for the 86% of those from age 15 and over who “can both read and write with understanding” is based on “a short simple statement on his/her everyday life” UNESCO

Initial Strategies

Text simplification
Symbol labels require text cleaning, removal of special characters, handling of ambiguous meaning, spelling correction and extraction of parts of speech (PoS) – Natural Language Processing

Sample thanks to Dundee University AAC project consent form

symbol sentence You please help see it works

Symbol to Concept Mapping

Concept based on the label to symbol linking ≈70% accurate.

Semantic Word Embedding

Google Spreadsheet with similarity rating

Google sheet analysis of symbol similarity to label

Results and Future Work

Image recognition needed, but the results may not always help with topic classification!

Semantic reasoning to provide related symbols based on common knowledge base improved to 85.47%

Car?

Thank You

To see the results of the work please visit Global Symbols (https://globalsymbols.com/)

This work has been part of an Alan Turing Pilot project about AI and Inclusion (https://www.turing.ac.uk/research/research-projects/ai-and-inclusion) coordinated by the Web Science Institute.