[PDF] Top 20 Data Driven Text Simplification
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Data Driven Text Simplification
... Automatic text simplification is the process of transforming a complex text into an equivalent version which would be easier to read or understand by a target audience, or easier to handle by ... See full document
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Inducing Information Structures for Data driven Text Analysis
... There is a widespread need for automated text analysis to be integrated into research methods for computational social science (e.g. Grimmer and Stewart, 2013). In order to analyze highly diverse content, ... See full document
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Metaphors in Text Simplification: To change or not to change, that is the question
... dictive of lexical simplification in general. We use parallel versions (“raw” and simplified) of news data from Newsela 1 , a company that produces professionally simplified news texts, in which we annotate ... See full document
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Can Text Simplification Help Machine Translation?
... Machine translation for under-resourced languages is facing a number of problems. First, there is not enough parallel data to build robust statistical machine translation (SMT) systems. Second, most of these ... See full document
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Text Simplification from Professionally Produced Corpora
... Newsela data are producing outputs more grammatically correct than the model trained with Wikipedia-Simple Wikipedia ...Wikipedia data seems to be producing slightly simpler ... See full document
7
Optimizing Statistical Machine Translation for Text Simplification
... exploit data with im- proved quality and enlarged quantity, namely, large- scale paraphrase rules automatically derived from bilingual corpora and a small amount of manual simplification data with ... See full document
16
Large-Scale Hierarchical Alignment for Data-driven Text Rewriting
... Evaluation metrics We report a diverse range of automatic metrics and statistics. SARI (Xu et al., 2016) is a recently proposed metric for text sim- plification which correlates well with simplicity in the output. ... See full document
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Exploring Neural Text Simplification Models
... Furthermore, we are interested to explore whether large scale pre-trained embeddings can improve text simplification models. Kauchak (2013) indi- cates that combining normal data with simplified ... See full document
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A Hybrid System for Spanish Text Simplification
... training data many relative clauses were not separa- ble, due to the overall sentence complexity which is much lesser in the corpus from which the test data was ... See full document
10
Semantic Structural Evaluation for Text Simplification
... training data available to them, annotated by the same anno- tators as the test ...structural simplification, but experiments on different types of ...the data was annotated by systems that ... See full document
12
Simple English Wikipedia: A New Text Simplification Task
... this data we ran preliminary experiments to learn a sentence-level simplification ...of text simplification as an English-to-English transla- tion ...the data set and the n-gram ... See full document
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Efficiency Metrics for Data Driven Models: A Text Summarization Case Study
... the data effi- ciency with performance or ...training data. This happens if its performance scores on increasing training data cuts are all very low, but grow very quickly from one assessment to the ... See full document
11
An Unsupervised Alignment Algorithm for Text Simplification Corpus Construction
... simplified text must stem from the original ...test data consisted of pairs of encyclo- pedia articles which presented a large intersection of factual information, but which was not necessar- ily presented ... See full document
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Design and Annotation of the First Italian Corpus for Text Simplification
... without a large quantity of aligned data. Hybrid ap- proaches seem to offer a good alternative; as shown by Siddharthan and Angrosh (2014), a system that combines automatically harvested lexical rules with ... See full document
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A Tagging Approach to Identify Complex Constituents for Text Simplification
... a text to select the best model for the genre, however this approach is limited to genres for which annotated data is ...using data from all ...available data produces a model with superior ... See full document
9
Neural Text Simplification of Clinical Letters with a Domain Specific Phrase Table
... The NTS system is trained on parallel Wikipedia and Simple Wikipedia documents. Whilst these may contain some medical texts, they are not spe- cific to the clinical genre and we should not ex- pect that direct ... See full document
10
Speech and Text driven Features for Automated Scoring of English Speaking Tasks
... The data used in this study comes from a large- scale English proficiency assessment for non- native speakers administered in multiple coun- tries. Each test-taker answers up to 6 questions: two general and four ... See full document
11
Text Simplification as Tree Labeling
... a simplification system that employs synchronous dependency grammars (Mandya et ...training data, which were not available to us, we cannot reproduce its ... See full document
7
Automatic Text Simplification for Spanish: Comparative Evaluation of Various Simplification Strategies
... comparable text simplification (TS) corpus (137,000 sentence pairs), the focus of the ATS for English was shifted towards data-driven ...of simplification present in the datasets ... See full document
9
A Customizable Editor for Text Simplification
... Lexical Simplification Data Set (Horn et ...English text for Hong Kong pupils, we used the vocabulary list from the Hong Kong Education Bureau (EDB, ... See full document
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