Research Goal
Make Web text so simple people understand it the first time they read it.
Background
Text comprises the vast majority of Web content. Poor reading comprehension presents significant challenges to many populations, including people with cognitive disabilities, non‐native speakers, and people with low literacy.
Text simplification aims to reduce text complexity while retaining its meaning. Manual text simplification research has been ongoing for decades. Yet no significant effort has been made to automate text simplification except as a preprocessor for natural-language processing tasks such as machine translation and summarization.
Short-Term Approach
In the short term, my partners and I are improving manual text simplification by creating effective, replicable methods for humans to produce it. We use national and international plain language standards. We conduct pilot studies to see if people comprehend our human-curated, simplified Web text better than typical Web text.
Long-Term Approach
In the long term, my partners and I are developing artificial intelligence (AI) capabilities to produce simple Web text on a mass scale. We are training AI with enormous sets of aligned sentence pairs (typical/simple). We will soon start crowd-sourcing the generation of training data.
I will provide details in future blog posts.