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Hits 1 – 18 of 18

1
Finding Concept-specific Biases in Form--Meaning Associations ...
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2
Modeling the Unigram Distribution ...
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3
A surprisal--duration trade-off across and within the world's languages ...
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4
Modeling the Unigram Distribution ...
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5
Finding Concept-specific Biases in Form–Meaning Associations ...
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6
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ...
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7
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ...
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8
How (Non-)Optimal is the Lexicon? ...
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9
Modeling the Unigram Distribution
In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (2021)
Abstract: The unigram distribution is the non-contextual probability of finding a specific word form in a corpus. While of central importance to the study of language, it is commonly approximated by each word’s sample frequency in the corpus. This approach, being highly dependent on sample size, assigns zero probability to any out-of-vocabulary (oov) word form. As a result, it produces negatively biased probabilities for any oov word form, while positively biased probabilities to in corpus words. In this work, we argue in favor of properly modeling the unigram distribution—claiming it should be a central task in natural language processing. With this in mind, we present a novel model for estimating it in a language (a neuralization of Goldwater et al.’s (2011) model) and show it produces much better estimates across a diverse set of 7 languages than the naïve use of neural character-level language models.
URL: https://hdl.handle.net/20.500.11850/518989
https://doi.org/10.3929/ethz-b-000518989
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10
Finding Concept-specific Biases in Form–Meaning Associations
In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021)
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11
How (Non-)Optimal is the Lexicon?
In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021)
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12
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs
In: Transactions of the Association for Computational Linguistics, 9 (2021)
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13
How (Non-)Optimal is the Lexicon? ...
NAACL 2021 2021; Blasi, Damián; Cotterell, Ryan. - : Underline Science Inc., 2021
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14
How (Non-)Optimal is the Lexicon? ...
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15
Finding Concept-specific Biases in Form--Meaning Associations ...
NAACL 2021 2021; Blasi, Damián; Cotterell, Ryan. - : Underline Science Inc., 2021
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16
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ...
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17
Speakers Fill Lexical Semantic Gaps with Context
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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18
Quantifying the Semantic Core of Gender Systems ...
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