Search Results for author: Sanja {\v{S}}tajner

Found 28 papers, 2 papers with code

Automated Text Simplification as a Preprocessing Step for Machine Translation into an Under-resourced Language

no code implementations RANLP 2019 Sanja {\v{S}}tajner, Maja Popovi{\'c}

We use the state-of-the-art automatic text simplification (ATS) system for lexically and syntactically simplifying source sentences, which are then translated with two state-of-the-art English-to-Serbian MT systems, the phrase-based MT (PBMT) and the neural MT (NMT).

Machine Translation Text Simplification +1

Effects of Lexical Properties on Viewing Time per Word in Autistic and Neurotypical Readers

no code implementations WS 2017 Sanja {\v{S}}tajner, Victoria Yaneva, Ruslan Mitkov, Simone Paolo Ponzetto

Eye tracking studies from the past few decades have shaped the way we think of word complexity and cognitive load: words that are long, rare and ambiguous are more difficult to read.

Lexical Simplification

Exploring Neural Text Simplification Models

1 code implementation ACL 2017 Sergiu Nisioi, Sanja {\v{S}}tajner, Simone Paolo Ponzetto, Liviu P. Dinu

Unlike the previously proposed automated TS systems, our neural text simplification (NTS) systems are able to simultaneously perform lexical simplification and content reduction.

Lexical Simplification Machine Translation +2

Bootstrapping a Hybrid MT System to a New Language Pair

no code implementations LREC 2016 Jo{\~a}o Ant{\'o}nio Rodrigues, Nuno Rendeiro, Andreia Querido, Sanja {\v{S}}tajner, Ant{\'o}nio Branco

The usual concern when opting for a rule-based or a hybrid machine translation (MT) system is how much effort is required to adapt the system to a different language pair or a new domain.

Machine Translation Translation

Use of Domain-Specific Language Resources in Machine Translation

no code implementations LREC 2016 Sanja {\v{S}}tajner, Andreia Querido, Nuno Rendeiro, Jo{\~a}o Ant{\'o}nio Rodrigues, Ant{\'o}nio Branco

In this paper, we address the problem of Machine Translation (MT) for a specialised domain in a language pair for which only a very small domain-specific parallel corpus is available.

Machine Translation Translation

Diachronic Changes in Text Complexity in 20th Century English Language: An NLP Approach

no code implementations LREC 2012 Sanja {\v{S}}tajner, Ruslan Mitkov

In British English, we compared the complexity of texts published in 1931, 1961 and 1991, while in American English we compared the complexity of texts published in 1961 and 1992.

Machine Translation Text Simplification

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