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1
Searching for More Efficient Dynamic Programs ...
Vieira, Tim; Cotterell, Ryan; Eisner, Jason. - : ETH Zurich, 2021
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2
Searching for More Efficient Dynamic Programs
In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021)
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3
A Corpus for Large-Scale Phonetic Typology ...
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4
A Corpus for Large-Scale Phonetic Typology ...
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5
A Corpus for Large-Scale Phonetic Typology
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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6
Contextualization of Morphological Inflection ...
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7
Are All Languages Equally Hard to Language-Model?
In: Proceedings of the Society for Computation in Linguistics (2019)
Abstract: How cross-linguistically applicable are NLP models, specifically language models? A fair comparison between languages is tricky: not only do training corpora in different languages have different sizes and topics, some of which may be harder to predict than others, but standard metrics for language modeling depend on the orthography of a language. We argue for a fairer metric based on the bits per utterance using utterance-aligned multi-text. We conduct a study on 21 languages, training and testing both n-gram and LSTM language models on “the same” set of utterances in each language (modulo translation), demonstrating that in some languages, especially those with complex inflectional morphology, the textual expression of the information is harder to predict.
Keyword: comparison; complexity; Computational Linguistics; language; language model; language-model; model; multilingual; nlp; rnn
URL: https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1048&context=scil
https://scholarworks.umass.edu/scil/vol2/iss1/47
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8
On the Complexity and Typology of Inflectional Morphological Systems
In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 327-342 (2019) (2019)
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9
On the Complexity and Typology of Inflectional Morphological Systems ...
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10
Are All Languages Equally Hard to Language-Model? ...
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11
A Deep Generative Model of Vowel Formant Typology ...
Cotterell, Ryan; Eisner, Jason. - : arXiv, 2018
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12
Unsupervised Disambiguation of Syncretism in Inflected Lexicons ...
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13
Quantifying the Trade-off Between Two Types of Morphological Complexity
In: Proceedings of the Society for Computation in Linguistics (2018)
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14
Probabilistic Typology: Deep Generative Models of Vowel Inventories ...
Cotterell, Ryan; Eisner, Jason. - : arXiv, 2017
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15
Probabilistic Typology: Deep Generative Models of Vowel Inventories ...
Cotterell, Ryan; Eisner, Jason. - : Apollo - University of Cambridge Repository, 2017
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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
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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
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18
Modeling Word Forms Using Latent Underlying Morphs and Phonology ...
Cotterell, Ryan; Peng, Nanyun; Eisner, Jason. - : Apollo - University of Cambridge Repository, 2015
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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
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