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Found 12 papers, 6 papers with code
Detection of Non-recorded Word Senses in English and Swedish
This study addresses the task of Unknown Sense Detection in English and Swedish.
DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages
Word meaning is notoriously difficult to capture, both synchronically and diachronically.
SuperSim: a test set for word similarity and relatedness in Swedish
Language models are notoriously difficult to evaluate.
Lexical semantic change for Ancient Greek and Latin
In this chapter we build on GASC, a recent computational approach to semantic change based on a dynamic Bayesian mixture model.
Challenges for Computational Lexical Semantic Change
The computational study of lexical semantic change (LSC) has taken off in the past few years and we are seeing increasing interest in the field, from both computational sciences and linguistics.
Topic modelling discourse dynamics in historical newspapers
This paper addresses methodological issues in diachronic data analysis for historical research.
An Unsupervised method for OCR Post-Correction and Spelling Normalisation for Finnish
Historical corpora are known to contain errors introduced by OCR (optical character recognition) methods used in the digitization process, often said to be degrading the performance of NLP systems.
SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection
Lexical Semantic Change detection, i. e., the task of identifying words that change meaning over time, is a very active research area, with applications in NLP, lexicography, and linguistics.
Dataset for Temporal Analysis of English-French Cognates
Languages change over time and, thanks to the abundance of digital corpora, their evolutionary analysis using computational techniques has recently gained much research attention.
From the Paft to the Fiiture: a Fully Automatic NMT and Word Embeddings Method for OCR Post-Correction
A great deal of historical corpora suffer from errors introduced by the OCR (optical character recognition) methods used in the digitization process.
Time-Out: Temporal Referencing for Robust Modeling of Lexical Semantic Change
State-of-the-art models of lexical semantic change detection suffer from noise stemming from vector space alignment.
GASC: Genre-Aware Semantic Change for Ancient Greek
Word meaning changes over time, depending on linguistic and extra-linguistic factors.
