A New Phonetic Candidate Generator for Improving Search Query Efficiency

摘要

Misspelled query due to homophones or mispronunciation is difficult to be corrected in the conventional spelling correction methods. In phonetic candidate generation, the generator is to produce candidates which are phonetically similar to a given query. In this paper, we present a new phonetic candidate generator for improving the search efficiency of a query. The proposed generator consists of three modules: letter-to-sound (LTS) conversion, phonetic "trie" and phonetic similarity estimator based upon Levenshtein distance and Kullback-Leibler Divergence (KLD) between phones. This generator yields a significant improvement over Double-metaphone in terms of candidate accuracy and effective candidate set size.