932 citations · 961 across the 11 of their papers we have counts for
8 papers · 1 filter
Taxi1500: A Multilingual Dataset for Text Classification in 1500 Languages
Chunlan Ma, Ayyoob ImaniGooghari, Haotian Ye +3
While natural language processing tools have been developed extensively for some of the world's languages, a significant portion of the world's over 7000 languages are still neglec…
The Touché23-ValueEval Dataset for Identifying Human Values behind Arguments
Nailia Mirzakhmedova, Johannes Kiesel, Milad Alshomary +11
We present the Touché23-ValueEval Dataset for Identifying Human Values behind Arguments. To investigate approaches for the automated detection of human values behind arguments, we…
Subword Sampling for Low Resource Word Alignment
Ehsaneddin Asgari, Masoud Jalili Sabet, Philipp Dufter +2
Annotation projection is an important area in NLP that can greatly contribute to creating language resources for low-resource languages. Word alignment plays a key role in this set…
Unsupervised Embedding-based Detection of Lexical Semantic Changes
Ehsaneddin Asgari, Christoph Ringlstetter, Hinrich Schütze
This paper describes EmbLexChange, a system introduced by the "Life-Language" team for SemEval-2020 Task 1, on unsupervised detection of lexical-semantic changes. EmbLexChange is d…
UniSent: Universal Adaptable Sentiment Lexica for 1000+ Languages
Ehsaneddin Asgari, Fabienne Braune, Benjamin Roth +2
In this paper, we introduce UniSent universal sentiment lexica for languages. Sentiment lexica are vital for sentiment analysis in absence of document-level annotations, a…
Past, Present, Future: A Computational Investigation of the Typology of Tense in 1000 Languages
Ehsaneddin Asgari, Hinrich Schütze
We present SuperPivot, an analysis method for low-resource languages that occur in a superparallel corpus, i.e., in a corpus that contains an order of magnitude more languages than…
Nonsymbolic Text Representation
Hinrich Schuetze, Heike Adel, Ehsaneddin Asgari
We introduce the first generic text representation model that is completely nonsymbolic, i.e., it does not require the availability of a segmentation or tokenization method that at…
Comparing Fifty Natural Languages and Twelve Genetic Languages Using Word Embedding Language Divergence (WELD) as a Quantitative Measure of Language Distance
Ehsaneddin Asgari, Mohammad R. K. Mofrad
We introduce a new measure of distance between languages based on word embedding, called word embedding language divergence (WELD). WELD is defined as divergence between unified si…