Unicode Normalization and Grapheme Parsing of Indic Languages

TL;DR

This paper introduces two tools—a normalizer and a grapheme parser—for better processing of Indic languages' complex orthographic units, improving accuracy over previous methods and supporting multiple scripts.

Contribution

It presents novel, efficient normalizer and parser tools tailored for Indic languages' complex graphemes, enhancing Unicode normalization and text processing capabilities.

Findings

Normalizer outperforms previous IndicNLP normalizer.

Tools effectively process seven Indic scripts.

Robust NLP experiments validate tool effectiveness.

Abstract

Writing systems of Indic languages have orthographic syllables, also known as complex graphemes, as unique horizontal units. A prominent feature of these languages is these complex grapheme units that comprise consonants/consonant conjuncts, vowel diacritics, and consonant diacritics, which, together make a unique Language. Unicode-based writing schemes of these languages often disregard this feature of these languages and encode words as linear sequences of Unicode characters using an intricate scheme of connector characters and font interpreters. Due to this way of using a few dozen Unicode glyphs to write thousands of different unique glyphs (complex graphemes), there are serious ambiguities that lead to malformed words. In this paper, we are proposing two libraries: i) a normalizer for normalizing inconsistencies caused by a Unicode-based encoding scheme for Indic languages and ii) a grapheme parser for Abugida text. It deconstructs words into visually distinct orthographic syllables or complex graphemes and their constituents. Our proposed normalizer is a more efficient and effective tool than the previously used IndicNLP normalizer. Moreover, our parser and normalizer are also suitable tools for general Abugida text processing as they performed well in our robust word-based and NLP experiments. We report the pipeline for the scripts of 7 languages in this work and develop the framework for the integration of more scripts.