Papers with readability assessment
Enriching Word Embeddings with Domain Knowledge for Readability Assessment (C18-1)
Copied to clipboard
| Challenge: | Existing word embedding models focus on syntactic or semantic relations of words, while ignoring reading difficulty. |
| Approach: | They propose a method which learns the word embedding for readability assessment . they extract the knowledge on word-level difficulty from three perspectives to construct a knowledge graph . |
| Outcome: | The proposed method is effective and potential, the authors show . they use the knowledge-enriched word embedding model on English and Chinese datasets . |
Prompt-based Learning for Text Readability Assessment (2023.findings-eacl)
Copied to clipboard
| Challenge: | Using a pre-trained seq2seq model, we can discern which text is more difficult from two given texts (pairwise). |
| Approach: | They propose to adapt a pre-trained seq2seq model to discern which text is more difficult from two given texts (pairwise). |
| Outcome: | The proposed model can be adapted to discern which text is more difficult from two given texts (pairwise). |
BasahaCorpus: An Expanded Linguistic Resource for Readability Assessment in Central Philippine Languages (2023.emnlp-main)
Copied to clipboard
| Challenge: | Current research on automatic readability assessment (ARA) has focused on improving the performance of models in high-resource languages such as English. |
| Approach: | They propose a hierarchical cross-lingual modeling approach that takes advantage of a language’s placement in the family tree to increase the amount of available training data. |
| Outcome: | The proposed model improves the performance of models in high-resource languages such as English and Hiligaynon, minasbate, Karay-a, and Rinconada. |
A Corpus for Automatic Readability Assessment and Text Simplification of German (2020.lrec-1)
Copied to clipboard
| Challenge: | Using monolingual-only data, we can automate readability assessment and text simplification of simplified language. |
| Approach: | They present a corpus for automatic readability assessment and automatic text simplification for German using parallel and monolingual data. |
| Outcome: | The proposed corpus is compiled from web sources and contains information on text structure, typography, font style, and images. |
CEFR-Based Sentence Difficulty Annotation and Assessment (2022.emnlp-main)
Copied to clipboard
| Challenge: | Controllable text simplification is a crucial assistive technique for language learning and teaching. |
| Approach: | They propose a sentence-level assessment model to handle unbalanced level distribution . previous studies have suggested that controllable text simplification is difficult to apply . |
| Outcome: | The proposed method outperforms baselines in readability assessment by scoring macro-F1 on the level assessment. |
A Unified Neural Network Model for Readability Assessment with Feature Projection and Length-Balanced Loss (2022.emnlp-main)
Copied to clipboard
| Challenge: | Traditional readability assessment models employ hundreds of linguistic features, but it is less explored for readability assessments. |
| Approach: | They propose a BERT-based model with feature projection and length-balanced loss to determine the difficulty level of a given text. |
| Outcome: | The proposed model achieves significant improvements over baseline models on three English benchmark datasets and one Chinese dataset. |
Trends, Limitations and Open Challenges in Automatic Readability Assessment Research (2022.lrec-1)
Copied to clipboard
| Challenge: | Readability assessment is the task of evaluating the reading difficulty of a given piece of text. |
| Approach: | They examine the common approaches used for automatic readability assessment and identify their shortcomings and some challenges for the future. |
| Outcome: | The proposed models are compared with existing models and are based on existing ones. |