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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 4 of 4 1 Quantifying Paradigm Shape in Spanish Verbs LeFevre, Grace. - : The Ohio State University, 2021 BASE Show details 2 Formalizing Inflectional Paradigm Shape with Information Theory LeFevre, Grace; Elsner, Micha; Sims, Andrea D In: Proceedings of the Society for Computation in Linguistics (2021) BASE Show details 3 Interpreting Sequence-to-Sequence Models for Russian Inflectional Morphology King, David L; Sims, Andrea D; Elsner, Micha In: Proceedings of the Society for Computation in Linguistics (2020) Abstract: Morphological inflection, as an engineering task in NLP, has seen a rise in the use of neural sequence-to-sequence models (Kann et al. 2016, Cotterell et al. 2018, Aharoni et al. 2017). While these outperform traditional systems based on edit rule induction, it is hard to interpret what they are learning in linguistic terms. We propose a new method of analyzing morphological sequence-to-sequence models which groups errors into linguistically meaningful classes, making what the model learns more transparent. As a case study, we analyze a seq2seq model on Russian, finding that semantic and lexically conditioned allomorphy (e.g. inanimate nouns like zavod `factory' and animates like otec `father' have different, animacy-conditioned accusative forms) are responsible for its relatively low accuracy. Augmenting the model with word embeddings as a proxy for lexical semantics leads to significant improvements in predicted wordform accuracy. Keyword: Computational Linguistics; error analysis; interpretability; morphology; sequence-to-sequence URL: https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1156&context=scil https://scholarworks.umass.edu/scil/vol3/iss1/39 BASE Hide details 4 Stop the Morphological Cycle, I Want to Get Off: Modeling the Development of Fusion Elsner, Micha; Johnson, Martha B.; Antetomaso, Stephanie... In: Proceedings of the Society for Computation in Linguistics (2020) BASE Show details

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