[PDF] Top 20 Unsupervised Neural Text Simplification
Has 10000 "Unsupervised Neural Text Simplification" found on our website. Below are the top 20 most common "Unsupervised Neural Text Simplification".
Unsupervised Neural Text Simplification
... the text both lexically and ...syntactic simplification and are lim- ited to splitting and/or truncating ...based simplification, data-driven ap- proaches were proposed like phrase-based SMT (Specia, ... See full document
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A Detailed Evaluation of Neural Sequence to Sequence Models for In domain and Cross domain Text Simplification
... In recent years, the problem of automated sentence simpli- fication has often been addressed as the monolingual ma- chine translation (MT) task of translating from original to simple sentences. The MT models used were, ... See full document
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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
Sentence Simplification with Memory Augmented Neural Networks
... of neural MT (Sutskever et ...exploring neural simplification with sequence to sequence (Seq2seq) models, also referred to as encoder-decoder ...and unsupervised lexical simplifi- cation ... See full document
7
Text Simplification as Tree Labeling
... Several approaches to sentence compression have been presented in the last decade. Knight and Marcu (2002) and Turner and Charniak (2005) ap- ply noisy channel models, using language models to control for grammaticality. ... See full document
7
Unsupervised Neural Dependency Parsing
... from text anno- tated with only POS ...to unsupervised dependen- cy parsing that uses a neural model to predict grammar rule probabilities based on distribut- ed representation of POS ... See full document
9
Lexical Simplification with Neural Ranking
... Lexical Simplification (LS), words and expres- sions that challenge a target audience are replaced with simpler ...con- text of the complex word; and Substitution Rank- ing (SR) to rank them according to ... See full document
7
Data Driven Text Simplification
... Sequence-to-sequence neural models (Nisioi et ...the neural model based on reinforcement learning techniques (Zhang and Lapata, 2017) showed a dominance of neural ATS approaches over the previous ... See full document
5
Automatic Text Simplification for Spanish: Comparative Evaluation of Various Simplification Strategies
... for text simpli- fication, the problem of coverage is not so much of an issue as it is in cross-lingual ...The unsupervised align- ment model implemented in Moses using GIZA++ aligner (Och and Ney, 2003) ... See full document
9
Controllable Text Simplification with Lexical Constraint Loss
... Text simplification can be regarded as a mono- lingual machine translation problem. Previ- ous studies have trained a model to trans- late complex sentences into simpler sentences on parallel corpora ... See full document
7
Metaphors in Text Simplification: To change or not to change, that is the question
... Lexical simplification systems often build on sentence-aligned simplification corpora and pro- pose substitutes for complex words from a num- ber of synonyms based on the words’ frequency, length and ... See full document
12
Unsupervised Controllable Text Formalization
... Automatic text style-transformation is one of the key goals of text-to-text natural language generation (NLG) research and most existing systems for such tasks are either super- vised ...Seq2Seq ... See full document
8
Neural Text Simplification in Low Resource Conditions Using Weak Supervision
... Simple-to-complex synthetic pairs creation: We convert the gold data into a set of simple-to- complex pairs inspired by the work in MT (Sen- nrich et al., 2016b) and in keyword-to-question (Ding and Balog, 2018), and ... See full document
8
Simple and Effective Text Simplification Using Semantic and Neural Methods
... first simplification system com- bining semantic structures and neural machine translation, showing that it outperforms existing lexical and structural ... See full document
12
Exploring Neural Text Simplification Models
... cal simplification (LS) was addressed by unsuper- vised approaches leveraging word-embeddings, with reported good success (Glavaˇs and ˇStajner, 2015; Paetzold and Specia, ... See full document
7
An Unsupervised Alignment Algorithm for Text Simplification Corpus Construction
... We consider that our task is not directly compara- ble to this previous work: the texts we are working with are direct simplifications of the source texts. So we can assume that all information in the simplified ... See full document
7
Can Text Simplification Help Machine Translation?
... automatic text simplification systems (ATS) can improve English-to-Serbian machine translation (MT) if used as a pre-processing step to simplify source sentences before translating them with the SMT ... See full document
13
Optimizing Statistical Machine Translation for Text Simplification
... Here we look more deeply at the correlations of BLEU and SARI with human judgments. Our SARI metric has highest correlation with human judg- ments of simplicity, but BLEU exhibits higher corre- lations on grammaticality ... See full document
16
Text Simplification from Professionally Produced Corpora
... Koehn, P., Hoang, H., Birch, A., Callison-Burch, C., Fed- erico, M., Bertoldi, N., Cowan, B., Shen, W., Moran, C., Zens, R., Dyer, C., Bojar, O., Constantin, A., and Herbst, E. (2007). Moses: Open source toolkit for ... See full document
7
Summarising News Stories for Children
... Automatic text summarisation is a research area with half a century of history, with Luhn (1958) discussing as far back as 1958 the task he called “auto-abstracting of ...of unsupervised and supervised ... See full document
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