Natural Language Processing
PhD in language technology
MA in computational linguistics
BA in linguistics and Italian
- Computer-based readability assessment
- Language resources
- Language accessibility
- NLP methods for augmentative and alternative communication (AAC)
- Text classification
- Corpus linguistics
Today most public services involve electronic communication, which requires that people are able to read relatively well. However, a significant number of adults cannot fully understand the texts they read for example on the internet. In my thesis I present a new model, called SVIT, that can be used as a tool to measure the readability of texts and therefore how appropriate they are for different target groups.
To measure the readability of a text, Sweden has relied on a readability index called LIX since 1968. The LIX measure indicates what a text looks like on the surface, or more exactly the average sentence length and the proportion of the words that are longer than six letters.
Today more modern language technology and digital language resources are allowing for more precise readability analyses. I have assessed previous studies on what it is in a text that affects different readers' ability to understand it. It may for example be a matter of word variation and sentence structure. My thesis investigates at which linguistic levels these features of a text are found, and whether they really differ to any measurable extent.
Present project work
From June 2013 involved in the project "Mining textual data for simplified reading", funded by Marcus and Amalia Wallenberg Foundation.
Biennial Language Resources and Evaluation Conference (LREC) 2006 - 2012
Language technology and text authoring tools within the Language Consultancy Program, spring semester 2013
Awarded scholarship for researchers by GU Holding at University of Gothenburg, 2010