Sarah Wayland


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Error Correction for Arabic Dictionary Lookup
C. Anton Rytting | Paul Rodrigues | Tim Buckwalter | David Zajic | Bridget Hirsch | Jeff Carnes | Nathanael Lynn | Sarah Wayland | Chris Taylor | Jason White | Charles Blake III | Evelyn Browne | Corey Miller | Tristan Purvis
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

We describe a new Arabic spelling correction system which is intended for use with electronic dictionary search by learners of Arabic. Unlike other spelling correction systems, this system does not depend on a corpus of attested student errors but on student- and teacher-generated ratings of confusable pairs of phonemes or letters. Separate error modules for keyboard mistypings, phonetic confusions, and dialectal confusions are combined to create a weighted finite-state transducer that calculates the likelihood that an input string could correspond to each citation form in a dictionary of Iraqi Arabic. Results are ranked by the estimated likelihood that a citation form could be misheard, mistyped, or mistranscribed for the input given by the user. To evaluate the system, we developed a noisy-channel model trained on studentsÂ’ speech errors and use it to perturb citation forms from a dictionary. We compare our system to a baseline based on Levenshtein distance and find that, when evaluated on single-error queries, our system performs 28% better than the baseline (overall MRR) and is twice as good at returning the correct dictionary form as the top-ranked result. We believe this to be the first spelling correction system designed for a spoken, colloquial dialect of Arabic.