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Found 21 papers, 2 papers with code
Measuring Translationese across Levels of Expertise: Are Professionals more Surprising than Students?
The present paper deals with a computational analysis of translationese in professional and student English-to-German translations belonging to different registers.
Some steps towards the generation of diachronic WordNets
We apply hyperbolic embeddings to trace the dynamics of change of conceptual-semantic relationships in a large diachronic scientific corpus (200 years).
Tracing variation in discourse connectives in translation and interpreting through neural semantic spaces
In the present paper, we explore lexical contexts of discourse markers in translation and interpreting on the basis of word embeddings.
Predicting Literary Quality How Perspectivist Should We Be?
Approaches in literary quality tend to belong to two main grounds: one sees quality as completely subjective, relying on the idiosyncratic nature of individual perspectives on the apperception of beauty; the other is ground-truth inspired, and attempts to find one or two values that predict something like an objective quality: the number of copies sold, for example, or the winning of a prestigious prize.
Ancient Greek WordNet Meets the Dynamic Lexicon: the Example of the Fragments of the Greek Historians
The Ancient Greek WordNet (AGWN) and the Dynamic Lexicon (DL) are multilingual resources to study the lexicon of Ancient Greek texts and their translations.
The diffusion of scientific terms – tracing individuals’ influence in the history of science for English
Tracing the influence of individuals or groups in social networks is an increasingly popular task in sociolinguistic studies.
Says Who? Effective Zero-Shot Annotation of Focalization
Focalization, the perspective through which narrative is presented, is encoded via a wide range of lexico-grammatical features and is subject to reader interpretation.
Good Books are Complex Matters: Gauging Complexity Profiles Across Diverse Categories of Perceived Literary Quality
In this study, we employ a classification approach to show that different categories of literary "quality" display unique linguistic profiles, leveraging a corpus that encompasses titles from the Norton Anthology, Penguin Classics series, and the Open Syllabus project, contrasted against contemporary bestsellers, Nobel prize winners and recipients of prestigious literary awards.
Sentiment Dynamics of Success: Fractal Scaling of Story Arcs Predicts Reader Preferences
We explore the correlation between the sentiment arcs of H. C. Andersen's fairy tales and their popularity, measured as their average score on the platform GoodReads.
How Human is Machine Translationese? Comparing Human and Machine Translations of Text and Speech
Some translationese features tend to appear in simultaneous interpreting with higher frequency than in human text translation, but the reasons for this are unclear.
Sky + Fire = Sunset. Exploring Parallels between Visually Grounded Metaphors and Image Classifiers
This work explores the differences and similarities between neural image classifiers{'} mis-categorisations and visually grounded metaphors - that we could conceive as intentional mis-categorisations.
Grammar and Meaning: Analysing the Topology of Diachronic Word Embeddings
The paper showcases the application of word embeddings to change in language use in the domain of science, focusing on the Late Modern English period (17-19th century).
The Effect of Context on Metaphor Paraphrase Aptness Judgments
We conduct two experiments to study the effect of context on metaphor paraphrase aptness judgments.
Predicting Human Metaphor Paraphrase Judgments with Deep Neural Networks
We propose a new annotated corpus for metaphor interpretation by paraphrase, and a novel DNN model for performing this task.
Bigrams and BiLSTMs Two Neural Networks for Sequential Metaphor Detection
We present and compare two alternative deep neural architectures to perform word-level metaphor detection on text: a bi-LSTM model and a new structure based on recursive feed-forward concatenation of the input.
``Deep'' Learning : Detecting Metaphoricity in Adjective-Noun Pairs
We show that using a single neural network combined with pre-trained vector embeddings can outperform the state of the art in terms of accuracy.
The Making of Ancient Greek WordNet
This paper describes the process of creation and review of a new lexico-semantic resource for the classical studies: AncientGreekWordNet.
