PHONETIC MATCHING TOOLKIT WITH STATE-OF-THE-ART META-SOUNDEX ALGORITHM (ENGLISH AND SPANISH)

Researchers confront major problems while searching for various kinds of data in large imprecise databases, as they are not spelled correctly or in the way they were expected to be spelled. As a result, they cannot find the word they sought. Over the years of struggle, pronunciation of words was considered to be one of the practices to solve the problem effectively. The technique used to acquire words based on sounds is known as “Phonetic Matching”. Soundex was the first algorithm developed and other algorithms like Metaphone, Caverphone, DMetaphone, Phonex etc., are also used for information retrieval in different environments. This project mainly deals with the analysis and implementation of newly proposed Meta-Soundex algorithm for English and Spanish languages which retrieves suggestions for the misspelled words.

The newly developed Meta-Soundex algorithm addresses the limitations of Metaphone and Soundex algorithms. Specifically, the new algorithm has more accuracy compared to both Soundex and Metaphone algorithm. The new algorithm also has higher precision compared to Soundex, thus reducing the noise in the considered arena. A phonetic matching toolkit is also developed enclosing the different phoneticmatching algorithms along with the state-of-the-art Meta-Soundex algorithm for both Spanish and English languages.