Between Sound and Spelling: Combining Phonetics and Clustering Algorithms to Improve Target Word Recovery

In this paper we revisit the task of spell checking focusing on target word recovery. We propose a new approach that relies on phonetic information to improve the accuracy of clustering algorithms in identifying misspellings and generating accurate suggestions. The use of phonetic information is not new to the task of spell checking and it was used successfully in previous approaches. The combination of phonetics and cluster-based methods for spell checking was to our knowledge not yet explored and it is the new contribution of our work. We report an improvement of 8.16% accuracy when compared to a previously proposed spell checking approach.