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Multiattentive Recurrent Neural Network Architecture for Multilingual Readability Assessment

Ion Madrazo Azpiazu, Maria Soledad Pera
2019 Transactions of the Association for Computational Linguistics  
We present a multiattentive recurrent neural network architecture for automatic multilingual readability assessment.  ...  of great importance to readability.  ...  A multilevel Basque readability assessment strategy that relies on random forest and linguistic features with a major emphasis on morphology and syntax (Madrazo, 2014) .  ... 
doi:10.1162/tacl_a_00278 fatcat:25rqdlm3anaujlmzsqo6j4oa7u

BERT Embeddings for Automatic Readability Assessment [article]

Joseph Marvin Imperial
2021 arXiv   pre-print
In this study, we propose an alternative way of utilizing the information-rich embeddings of BERT models with handcrafted linguistic features through a combined method for readability assessment.  ...  Automatic readability assessment (ARA) is the task of evaluating the level of ease or difficulty of text documents for a target audience.  ...  As for the dataset, for Adarna House, permission was obtained from the publishing house while for the OSE and CCE datasets, it remains open-sourced.  ... 
arXiv:2106.07935v2 fatcat:ywondj4e3bfcxetsnd4ks7u7ea

Modeling Local Coherence: An Entity-Based Approach

Regina Barzilay, Mirella Lapata
2008 Computational Linguistics  
We re-conceptualize coherence assessment as a learning task and show that our entity-based representation is well-suited for ranking-based generation and text classification tasks.  ...  Using the proposed representation, we achieve good performance on text ordering, summary coherence evaluation, and readability assessment.  ...  We are grateful to Claire Cardie and Vincent Ng for providing us the results of their coreference system on our data.  ... 
doi:10.1162/coli.2008.34.1.1 fatcat:fvu7vlytwrbmhhyhx3jixs2gl4

Application of Computational Linguistics to Predicting Language Proficiency Level of Persian Learners' Textbooks

Masood Ghayoomi
2022 Journal of language horizons  
The performance of the models vary based on the learning algorithm and the feature set(s) used for training the models.  ...  To this end, a corpus is developed from Persian learners' textbooks and statistical and linguistic features are extracted from this text corpus to train three classifiers as learners.  ...  Acknowledgement This research is funded by Iran National Science Foundation (INSF) for the research proposal number 97000696.  ... 
doi:10.22051/lghor.2021.32656.1354 doaj:3b5a424d0cfd467eae26ef34a8aa52ca fatcat:44j6omndujcsdf5lx5opxncawm

Text Complexity Classification Data Mining Model Based on Dynamic Quantitative Relationship between Modality and English Context

Dan Zhang, Gengxin Sun
2021 Mathematical Problems in Engineering  
After that, based on computational linguistics and mathematical-statistical analysis, combined with machine learning and information retrieval technology, the text in any format is converted into a content  ...  format that can be used for machine learning, and patterns or knowledge are derived from this content format.  ...  For statistical language model design characteristics of knowledge domain experts combined features, a smooth unary model is constructed for each readability can often has a high correlation with  ... 
doi:10.1155/2021/4805537 fatcat:zfnleith7vcwjbkokxkcfprhaq

Linguistic Features for Readability Assessment [article]

Tovly Deutsch, Masoud Jasbi, Stuart Shieber
2020 arXiv   pre-print
Readability assessment aims to automatically classify text by the level appropriate for learning readers.  ...  Our results provide preliminary evidence for the hypothesis that the state-of-the-art deep learning models represent linguistic features of the text related to readability.  ...  For this reason, in this paper we attempt to incorporate linguistic features with deep learning methods in order to improve readability assessment.  ... 
arXiv:2006.00377v1 fatcat:jahsozohwvbbjfykv7pj6gh3cq

Text complexity and linguistic features: Their correlation in English and Russian

Dmitry A. Morozov, Anna V. Glazkova, Boris L. Iomdin
2022 Russian Journal of Linguistics  
For many years, simple features were used to assess readability, e.g. average length of words and sentences or vocabulary variety.  ...  We experimentally assessed seven commonly used feature types (readability, traditional features, morphological features, punctuation, syntax frequency, and topic modeling) on six corpora for text complexity  ...  Linguistic Features According to the related works, we identified seven types of features, which can be used to assess the text complexity: 1) readability indices, e.g., the Flesch-Kincaid readability  ... 
doi:10.22363/2687-0088-30132 doaj:4c45eafccba2425791ef5a7af4465b36 fatcat:xc6lfb5iz5bk7lwjye3ovbmyye

Text as Environment: A Deep Reinforcement Learning Text Readability Assessment Model [article]

Hamid Mohammadi, Seyed Hossein Khasteh
2019 arXiv   pre-print
Deep reinforcement learning models are demonstrated to be helpful in further improvement of state-of-the-art text readability assessment models.  ...  The formulation of text readability assessment demands the identification of meaningful properties of the text and correct conversion of features to the right readability level.  ...  features used in early machine learning models for text readability assessment like works presented in [27, 32] .  ... 
arXiv:1912.05957v2 fatcat:zg5mzwwld5hn3mbxigudopmble

Pushing on Text Readability Assessment: A Transformer Meets Handcrafted Linguistic Features [article]

Bruce W. Lee, Yoo Sung Jang, Jason Hyung-Jong Lee
2021 arXiv   pre-print
We report two essential improvements in readability assessment: 1. three novel features in advanced semantics and 2. the timely evidence that traditional ML models (e.g.  ...  Then, we extract 255 handcrafted linguistic features using self-developed extraction software.  ...  Introduction The long quest for advancing readability assessment (RA) mostly centered on handcrafting the linguistic features that affect readability (Pitler and Nenkova, 2008) .  ... 
arXiv:2109.12258v1 fatcat:6sdnrkkzrjanjnqmrgo5bqwgke

Text analysis in financial disclosures [article]

Sridhar Ravula
2021 arXiv   pre-print
Specifically, it focuses on research related to text source, linguistic attributes, firm attributes, and mathematical models employed in the text analysis approach.  ...  It also explores the state of art methods in computational linguistics and reviews the current methodologies in Natural Language Processing (NLP).  ...  They proposed an analytical pipeline for identifying FLSs and extracting linguistics features, including topics, sentiments, readability, semantic similarity, and general text features.  ... 
arXiv:2101.04480v1 fatcat:bdbynvfhrjaapaan5m3qnjtcne

Stylene: an Environment for Stylometry and Readability Research for Dutch [chapter]

2017 CLARIN in the Low Countries  
The Stylene system consists of a popularisation interface for learning about stylometric analysis, and of web-based interfaces to so ware for readability and stylometry research aimed at researchers from  ...  readability research for Dutch) project.  ...  For the actual assessments, two web applications were designed to collect readability assessments for Dutch and English texts: one that is intended exclusively for language experts and one that is open  ... 
doi:10.5334/bbi.16 fatcat:e4v6z5p4dncetfk2gvrjyn4fdm

Building a Corpus of 2L English for Automatic Assessment: The CLEC Corpus

Ma Ángeles Zarco Tejada, Carmen Noya Gallardo, Ma Carmen Merino Ferradá, Ma Isabel Calderón López
2015 Procedia - Social and Behavioral Sciences  
levels and formed to train statistical models for automatic proficiency assessment.  ...  In this paper we describe the CLEC corpus, an ongoing project set up at the University of Cádiz with the purpose of building up a large corpus of English as a 2L classified according to CEFR proficiency  ...  We also thank the Teaching Innovation Section of the University of Cádiz for having financed this project.  ... 
doi:10.1016/j.sbspro.2015.07.474 fatcat:sjjvutpiwzeizj3pz4xz5sn2ni

Cognitively Driven Arabic Text Readability Assessment Using Eye-Tracking

Ibtehal Baazeem, Hend Al-Khalifa, Abdulmalik Al-Salman
2021 Applied Sciences  
for readability assessment tasks.  ...  Previous cognitive psychology literature shows that readable and difficult-to-read texts are associated with certain eye movement patterns, which has recently encouraged researchers to use these patterns  ...  Additionally, the authors would like to thank the Applied Linguistics Research Lab at Prince Sultan University, Riyadh, Saudi Arabia, for facilitating eye-tracking data collection.  ... 
doi:10.3390/app11188607 fatcat:j65cku3ypnenvk5zttduytqffu

Automatic proficiency classification in L2 Portuguese

Iria del Río
2019 Revista de Procesamiento de Lenguaje Natural (SEPLN)  
We use supervised learning and we approach the task as a classification problem, using the CEFR scale. Different linguistic features are tested, combined with different algorithms.  ...  With the best model, we get an accuracy of 72%, a result in line with previous experiments with other languages.  ...  The availability of data with linguistic annotations benefits different types of research, from theoretical analysis to statistical approaches like Machine Learning.  ... 
dblp:journals/pdln/Rio19 fatcat:bz4srht3gjdstnomh4tqnce7kq

Estimating Linguistic Complexity for Science Texts

Farah Nadeem, Mari Ostendorf
2018 Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications  
Existing work on automated text complexity analysis uses linear models with engineered knowledge-driven features as inputs.  ...  Traditional readability metrics have the additional drawback of not generalizing to informational texts such as science.  ...  Vajjala-Balakrishna, Assistant Professor Iowa State University, for sharing the WeeBit training corpus, their trained readability assessment model and the Common Core test corpus.  ... 
doi:10.18653/v1/w18-0505 dblp:conf/bea/NadeemO18 fatcat:dzjt2upb2vbtrlq4t7djxno2kq
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