Essays about: "diachronic word embeddings"
Found 4 essays containing the words diachronic word embeddings.
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1. WANNA BE ON TOP? The Hyperparameter Search for Semantic Change's Next Top Model
University essay from Göteborgs universitet / Institutionen för filosofi, lingvistik och vetenskapsteoriAbstract : Lexical semantic change (LSC) detection through the use of diachronic corpora and computational methods continues to be a prevalent research area in language change (Tahmasebi et al., 2018). READ MORE
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2. Investigating Gender Bias in Word Embeddings for Chinese
University essay from Uppsala universitet/Institutionen för lingvistik och filologiAbstract : Gender bias, a sociological issue, has attracted the attention of scholars working on natural language processing (NLP) in recent years. It is confirmed that some NLP techniques like word embedding could capture gender bias in natural language. Here, we investigate gender bias in Chinese word embeddings. READ MORE
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3. Unsupervised Lexical Semantic Change Detection with Context-Dependent Word Representations
University essay from Uppsala universitet/Institutionen för lingvistik och filologiAbstract : In this work, we explore the usefulness of contextualized embeddings from language models on lexical semantic change (LSC) detection. With diachronic corpora spanning two time periods, we construct word embeddings for a selected set of target words, aiming at detecting potential LSC of each target word across time. READ MORE
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4. Detecting Lexical Semantic Change Using Probabilistic Gaussian Word Embeddings
University essay from Uppsala universitet/Institutionen för lingvistik och filologiAbstract : In this work, we test two novel methods of using word embeddings to detect lexical semantic change, attempting to overcome limitations associated with conventional approaches to this problem. Using a diachronic corpus spanning over a hundred years, we generate word embeddings for each decade with the intention of evaluating how meaning changes are represented in embeddings for the same word across time. READ MORE
