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- W1580178421 abstract "Uninhabited mistakes while writing happens are unstoppable. There are certain common errors that occur during writing such as missing letters, extra letters, disordered letters, and misspelled letters. These kind of common spelling errors are called phonetics spelling errors. These are of a major concern while dealing with phonetics. Out of various problems that the phoneticians are trying to solve, major portion of it concentrates on varieties of spelling errors. Phonetic structures are greatly emphasized based on the effectiveness, appropriateness and accuracy. In order to keep abreast with the changing and challenging trends of Natural Language Processing (NLP), it is of great importance that one should resolve the problems of spelling errors. To achieve the goal, numerous realistic and practical approaches have to be adopted that make use of spelling correction algorithms such as Edit distance, Habit distance, Soundex and Asoundex. Through the analysis of these algorithms, a new interface is put forward that calculates the Edit distance, thereby showing the overall comparative study of phonetic algorithms with the proposed modified Edit Distance algorithm. The interface computes the Edit distance between two strings in appropriate and intuitive way, contemplating with the comparisons shown in the distance table. The Results show that an average of 0.937 recall and 0.947 precision have been achieved with the F-measure 0.9417. Through these results, it is evident that the recall and F-measures are improved in the proposed Edit-Distance algorithm. The revised version of the edit distance algorithm consistently attains finer quality results in comparison with the traditional edit distance algorithm." @default.
- W1580178421 created "2016-06-24" @default.
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- W1580178421 date "2015-01-01" @default.
- W1580178421 modified "2023-09-27" @default.
- W1580178421 title "Metrics for evaluating phonetics machine translation in Natural Language Processing through modified Edit Distance algorithm-A naïve approach" @default.
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- W1580178421 doi "https://doi.org/10.1109/iccci.2015.7218113" @default.
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