Cost of error correction quantification with Bengali text transcription

Abstract

Text based interaction in user mother language becomes one of the most primitive and usable interaction technique with the gigantic growth of the digital communication application like e-mailing, messaging, chatting, blogging etc. Efficiency of a text entry technology mainly depends on text entry rate and error rate. Number of errors occurs during typing are generally measured by Levenshtein minimum string distance (MSD) statistic. It counts the number of error present in transcribed text concerning presented text and quantifies the numbers of single edit operation required to transform transcribed text to presented text. It reckons one single edit operation for one error. However, it is not applicable to Indian languages to error correction operation quantification due to language-related features like — complex (‘juktakkhor’) and matra characters. As single error in a complex character may required multiple single edit operations to correct. The error on complex character is basically confined the practical usefulness of MSD quantification method in Indian language scenario. In this paper, we quantify the minimum number of single edit primitive required to correct the errors in Indian language transcribed text typed by any single stroke or tap text entry tool. To accomplish our objective, initially, we identify the mismatched character (error) positions in both transcribed and presented text both by employing longest common subsequence (LCS) algorithm. Then, we proposed an algorithm to identify whether error in simple character or in complex character. After that, we propose another algorithm to calculate the minimum number of operations to renovate transcribed to presented text depending upon error positions and type (error in simple or complex character). Lastly, we define correction cost per error (CCPE) metric to calculate average correction cost for an erroneous transcribed text.