Context-aware correction of spelling errors in hungarian medical documents

Authors:
Borbála Siklósi;Attila Novák;Gábor Prószéky
Affiliations:
Faculty of Information Technology, Pázmány Péter Catholic University, Budapest, Hungary;MTA-PPKE Language Technology Research Group, Hungary,Faculty of Information Technology, Pázmány Péter Catholic University, Budapest, Hungary;MTA-PPKE Language Technology Research Group, Hungary,Faculty of Information Technology, Pázmány Péter Catholic University, Budapest, Hungary
Venue:
SLSP'13 Proceedings of the First international conference on Statistical Language and Speech Processing
Year:
2013

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Abstract

In our paper, we present a method for automated correction of spelling errors in Hungarian clinical records. We model the problem of spelling correction as a translation task, where the source language is the erroneous text and the target language is the corrected one using an SMT decoder to perform the error correction. Since no orthographically correct proofread text from this domain is available, we cannot use such a corpus for training the system, instead a spelling correction generation and ranking system is used to create translation models. In addition, a language model is used in order to model lexical context. We show that our system outperforms the first candidate accuracy of the baseline ranking system.