A rabic Word-level Readability Visualization for Assisted Text Simplification (2022)

Abstract: This demo paper presents a Google Docs add-on for automatic Arabic word-level readability visualization. The add-on includes a lemmatization component that is connected to a five-level readability lexicon and Arabic WordNet-based substitution suggestions. The add-on can be used for assessing the reading difficulty of a text and identifying difficult words as part of the task of manual text simplification. We make our add-on and its code publicly available.

## introduction models for automatic readability assessment and automatic text simplification are relevant to many natural language processing (nlp) tasks such as developing pedagogical language technologies that assist students with learning languages, or teachers with curriculum design and writing assessment, as well as personalized paraphrasing of nlp systems' outputs to target different users with different readability levels. developing robust models for readability assessment and simplification requires the creation of large-scale lexical and annotated resources for training and evaluation. for example, parallel texts with different paired readability levels can be used to train readability models as well as simplification models. figure 1 presents an example from an arabic novel paired with a simplified version targeting the fifth-grade readability level. properly identifying which words and phrases need to be rewritten in a simplified manner for a specific target readability level and audience requires word-level readability annotation in a framework that enables easy editing of the original text, as well as easy checking on the updated text. to our knowledge, most of the available tools for readability assessment work on the document or the sentence levels. the system presented in this paper addresses this limitation by focusing on word-level readability visualization to assist human annotators working on identifying text readability levels and adjusting texts to simplify them in a controlled setting. this effort is part of a project on the simplification of arabic masterpieces for extensive reading (samer) @xcite @xcite . the project goals include the creation of a lemma-based graded readability lexicon for arabic and a corpus of parallel original and simplified texts from arabic novels (such as those presented in figure 1 ). the project plans to target two different simplified readability levels: grades 4-5 (level iii) and grades 6-8 (level iv). while our focus is on arabic, a language with limited annotated resources for text simplification, the components we developed can be easily extended to other languages. the demo system is a google docs add-on that includes morphological analysis and light disambiguation of arabic text, visualization of word readability levels, and access to substitution options with their own explicit readability levels. we make our add-on and its code publicly available. 1,2 next, we present some relevant arabic linguistic facts ( §2), and discuss related work ( §3). we then present our design and implementation decisions ( §4). in §5 we discuss some examples and use cases. ## relevant arabic linguistic facts modern standard arabic (msa) poses many challenges for nlp tasks @xcite . two in particular are directly relevant to the task at hand, and affect many of our design decisions: morphological richness and orthographic ambiguity. 3 morphological richness arabic employs a combination of templatic, affixational, and cliticization morphological operations to realize a large number of features such as gender, number, person, case, state, aspect, voice, and mood, in addition to a number of attachable pronominal, preposition and determiner clitics. this leads to a very large number of words to model. to address this aspect, we utilize a morphological analysis component that is optimized for efficient representation @xcite . ## samer add-on: examples and use cases we present some examples of how the samer project google docs add-on can be used to analyze the readability of a literary text. we also discuss potential use cases of our tool across a variety of tasks and how it can be extended to other languages. examples figure 3 shows the result of using the tool to analyze a short segment of a novel. after clicking on the doc level button at the top, the tool highlights each word according to its readability level using different colors, and presents a summary distribution of words in each readability level. figure 5 shows the result of selecting a specific word ( anhlt 'be disbanded') and clicking on the word level button at the top. a side bar appears showing the different lemma analyses by readability level. various word substitution alternatives are presented to the user including synonyms, hypernyms and hyponyms, with their associated readability levels. if the user decides to change the word, they can simply rewrite it and rerun the readability analysis. if the user decides to change the automatically assigned readability level, they can either change it directly manually, or by clicking on the assign button to change that specific word's readability level markup or the assign all button to change all of its occurrences in the document. use cases our goal behind creating an easy-touse google docs add-on tool for arabic word-level readability analysis is to enable users to edit texts easily based on a specific target readability level. we intend for our tool to be used by human annotators to identify text readability levels and to simplify texts in a controlled setting. however, we envision that our tool can be used to assist writers in either making texts more sophisticated (harder readability) or in providing alternatives for specific words that have the same readability level. extending to other languages although our work focuses on arabic, the samer add-on tool is designed in a modular way and it can be easily extended to other languages. more concretely, the following core components are needed to make such an extension possible: (1) a readability level lexicon that relates lemmas to their readability levels; ## conclusion we presented a google docs add-on for automatic arabic word-level readability visualization. our add-on includes a lemmatization component that is connected to a five-level readability lexicon and arabic wordnet-based substitution suggestions. the add-on can be used for assessing the reading difficulty of a text and identifying difficult words as part of the task of manual text simplification. in future work, we plan on enhancing our tool's readability analysis by leveraging additional morphosyntatic features @xcite . we will use the add-on to annotate a corpus of parallel original and simplified texts from arabic novels.