1. Customized Spell Corrector
Aviad Ashkenazi
Matan Zinger
March 2012

2. Agenda Overview about Dysgraphia
Short overview of Natural Language Processing
Using NLP to solve Dysgraphia symptoms
Dispeller Application Demonstration

3. Overview – Cognitive Writing Process
Dysgraphia may caused by a “damage” in any of this modules.

4. Overview – Different Types of Dysgraphia
Surface Dysgraphia – damage in lexical flow
Using sub-lexical flow instead
Symptoms: replacing homo-phonetic letters, difficulty in irregular words
No mistakes will appear for univalent words
Similar symptoms will appear for children (w/o dysgraphia)
Phonological Dysgraphia – damage in sub-lexical flow
Difficulty in writing non-familiar words (which require translation of phoneme into grapheme)
No mistakes when using lexical flow (e.g. for familiar words)
Peripheral Dysgraphia – damage in grapheme buffer
Word length is one of the most critical factors
Symptoms: re-ordering of internal letters, doubling letters, omitting letters

5. Overview – Natural Language Processing
Purpose:
Machine’s understanding of human-generated text
Common terminology:
Tokenization
Lemmatization / Stemming
“Stop Words”
Part of Speech Tagging
Text Search, TF-IDF
Levenshtein Distance
For spell checking / fuzzy search
Ranking by the level of distance
Semantic Understanding
Popular Open-Source Library: Lucene.NET
Provides many generic NLP capabilities

6. NLP to Solve Dysgraphia Symptoms
Regular spell checker
For which cases will it work well?
Is it good enough for Dysgraphia?
Customized spell checker
How will it work?
What is required?
Isn’t it better?
Symptoms we chose to handle
Homophonic replacement of letters (“Dyscravia”)
Doubling letters (Grapheme Buffer Dysgraphia)
Changing internal order (Grapheme Buffer Dysgraphia)

7. The Dyspeller Application
Classification Module
Use a series of tests (presented as a “game”)
Determines “Dysgraphia Profile” – common symptoms
Personalized Spell Checker
For every misspelled word, we look for the nearest correct word
Search is done not by Levenshtein distance, but by “Personalized Dysgraphia Distance”
The distance between two words is calculated by:
Number of Dysgraphia symptoms which are typical for this specific user, that are needed to be fixed in order to generate word A from word B.
Publishing Module
The corrected text can be sent via SMS or to any of the contacts.

8. Dyspeller - Design Suggestion Processing –
Calculating Dysgraphia Distance
HTTP/GET:
Suggestions by symptoms
Double Letter Symptom
Internal Reorder Symptom
Phonetic Replace Symptom
Valid Words Data Set
Response:
misspelled word -> suggestions list
(JSON format)

9. DEMO

10. Thank You. References: Gvion, Friedmann, Yachini – Dysgraphia (2008)
Letter position dysgraphia (Aviah Gvion, Naama Friedmann) – 2009
Dyscravia: Voicing substitution dysgraphia (Aviah Gvion, Naama Friedmann) – 2010