Abstract
Text normalization is the challenge of discovering the English words corresponding to the unusually-spelled words used in social-media messages and posts. In this paper, we detail a new word-searching strategy based on the idea of sounding out the consonants of the word. We describe our algorithm to extract the base consonant information from both miswritten and real words using a spelling and a phonetic approach. We then explain how this information is used to match similar words together. This strategy is shown to be time efficient as well as capable of correctly handling many types of normalization problems.
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Jahjah, V., Khoury, R., Lamontagne, L. (2016). Word Normalization Using Phonetic Signatures. In: Khoury, R., Drummond, C. (eds) Advances in Artificial Intelligence. Canadian AI 2016. Lecture Notes in Computer Science(), vol 9673. Springer, Cham. https://doi.org/10.1007/978-3-319-34111-8_23
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DOI: https://doi.org/10.1007/978-3-319-34111-8_23
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