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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 – 19 of 19 1 Searching for More Efficient Dynamic Programs ... Vieira, Tim; Cotterell, Ryan; Eisner, Jason. - : ETH Zurich, 2021 BASE Show details 2 Searching for More Efficient Dynamic Programs Cotterell, Ryan; Eisner, Jason; Vieira, Tim In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021) BASE Show details 3 A Corpus for Large-Scale Phonetic Typology ... Salesky, Elizabeth; Chodroff, Eleanor; Pimentel, Tiago. - : arXiv, 2020 BASE Show details 4 A Corpus for Large-Scale Phonetic Typology ... Salesky, Elizabeth; Chodroff, Eleanor; Pimentel, Tiago. - : ETH Zurich, 2020 BASE Show details 5 A Corpus for Large-Scale Phonetic Typology Chodroff, Eleanor; Cotterell, Ryan; Wiesner, Matthew... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 6 Contextualization of Morphological Inflection ... Vylomova, Ekaterina; Cotterell, Ryan; Baldwin, Timothy. - : arXiv, 2019 BASE Show details 7 Are All Languages Equally Hard to Language-Model? Cotterell, Ryan; Mielke, Sebastian J; Eisner, Jason... In: Proceedings of the Society for Computation in Linguistics (2019) BASE Show details 8 On the Complexity and Typology of Inflectional Morphological Systems Cotterell, Ryan; Kirov, Christo; Hulden, Mans... In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 327-342 (2019) (2019) BASE Show details 9 On the Complexity and Typology of Inflectional Morphological Systems ... Cotterell, Ryan; Kirov, Christo; Hulden, Mans. - : arXiv, 2018 BASE Show details 10 Are All Languages Equally Hard to Language-Model? ... Cotterell, Ryan; Mielke, Sabrina J.; Eisner, Jason. - : arXiv, 2018 BASE Show details 11 A Deep Generative Model of Vowel Formant Typology ... Cotterell, Ryan; Eisner, Jason. - : arXiv, 2018 BASE Show details 12 Unsupervised Disambiguation of Syncretism in Inflected Lexicons ... Cotterell, Ryan; Kirov, Christo; Mielke, Sabrina J.. - : arXiv, 2018 BASE Show details 13 Quantifying the Trade-off Between Two Types of Morphological Complexity Cotterell, Ryan; Kirov, Christo; Hulden, Mans... In: Proceedings of the Society for Computation in Linguistics (2018) BASE Show details 14 Probabilistic Typology: Deep Generative Models of Vowel Inventories ... Cotterell, Ryan; Eisner, Jason. - : arXiv, 2017 BASE Show details 15 Probabilistic Typology: Deep Generative Models of Vowel Inventories ... Cotterell, Ryan; Eisner, Jason. - : Apollo - University of Cambridge Repository, 2017 BASE Show details 16 Probabilistic Typology: Deep Generative Models of Vowel Inventories Eisner, Jason; Cotterell, Ryan. - : Association for Computational Linguistics, 2017. : Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2017 BASE Show details 17 Weighting Finite-State Transductions With Neural Context Eisner, Jason; Cotterell, Ryan; Rastogi, Pushpendre. - : Association for Computational Linguistics, 2016. : Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2016 BASE Show details 18 Modeling Word Forms Using Latent Underlying Morphs and Phonology ... Cotterell, Ryan; Peng, Nanyun; Eisner, Jason. - : Apollo - University of Cambridge Repository, 2015 BASE Show details 19 Modeling Word Forms Using Latent Underlying Morphs and Phonology Eisner, Jason; Cotterell, Ryan; Peng, Nanyun. - : MIT Press, 2015. : Transactions of the Association for Computational Linguistics (TACL) 2015, 2015 Abstract: The observed pronunciations or spellings of words are often explained as arising from the “underlying forms” of their mor- phemes. These forms are latent strings that linguists try to reconstruct by hand. We propose to reconstruct them automatically at scale, enabling generalization to new words. Given some surface word types of a concatenative language along with the abstract morpheme sequences that they ex- press, we show how to recover consistent underlying forms for these morphemes, together with the (stochastic) phonology that maps each concatenation of underly- ing forms to a surface form. Our technique involves loopy belief propagation in a nat- ural directed graphical model whose vari- ables are unknown strings and whose con- ditional distributions are encoded as finite- state machines with trainable weights. We define training and evaluation paradigms for the task of surface word prediction, and report results on subsets of 7 languages. URL: https://doi.org/10.17863/CAM.41589 https://www.repository.cam.ac.uk/handle/1810/294483 BASE Hide details

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