An Evaluation of Phonetic Spell Checkers

In the work reported here, we describe a phonetic spell-checking algorithm integrating aspects of Soundex and Phonix. We increase the number of letter codes compared to Soundex and Phonix. We also integrate phonetic rules but use far less than Phonix where retrieval may be slow due to the computational cost of comparing the input to a large list of transformation rules. Our algorithm aims to repair spelling errors where the user has substituted homophones in place of the correct spelling. We evaluate our algorithm by comparing it to three alternative spell-checking algorithms and three benchmark spell checkers (MS Word 97 & 2000 and UNIX `ispell') using a list of phonetic spelling errors. We find that our approach has superior recall (percentage of correct matches retrieved) to the alternative approaches although the higher recall is at the expense of precision (number of possible matches retrieved). We intend our phonetic spell checker to be integrated into an existing spell checker so the precision will be improved by integration thus high recall is the aim for our approach in this paper.