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1
Probing for the Usage of Grammatical Number ...
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2
On Homophony and Rényi Entropy ...
Abstract: Homophony’s widespread presence in natural languages is a controversial topic. Recent theories of language optimality have tried to justify its prevalence, despite its negative effects on cognitive processing time, e.g., Piantadosi et al. (2012) argued homophony enables the reuse of efficient wordforms and is thus beneficial for languages. This hypothesis has recently been challenged by Trott and Bergen (2020), who posit that good wordforms are more often homophonous simply because they are more phonotactically probable. In this paper, we join in on the debate. We first propose a new information-theoretic quantification of a language’s homophony: the sample Rényi entropy. Then, we use this quantification to revisit Trott and Bergen’s claims. While their point is theoretically sound, a specific methodological issue in their experiments raises doubts about their results. After addressing this issue, we find no clear pressure either towards or against homophony—a much more nuanced result than either Piantadosi ... : Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing ...
URL: https://dx.doi.org/10.3929/ethz-b-000518993
http://hdl.handle.net/20.500.11850/518993
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3
On Homophony and Rényi Entropy ...
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4
On Homophony and Rényi Entropy ...
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5
Finding Concept-specific Biases in Form--Meaning Associations ...
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6
Quantifying Gender Bias Towards Politicians in Cross-Lingual Language Models ...
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7
Revisiting the Uniform Information Density Hypothesis ...
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8
Revisiting the Uniform Information Density Hypothesis ...
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9
Modeling the Unigram Distribution ...
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10
A Bayesian Framework for Information-Theoretic Probing ...
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11
A surprisal--duration trade-off across and within the world's languages ...
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12
Revisiting the Uniform Information Density Hypothesis ...
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13
What About the Precedent: An Information-Theoretic Analysis of Common Law ...
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14
Modeling the Unigram Distribution ...
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15
Finding Concept-specific Biases in Form–Meaning Associations ...
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16
How (Non-)Optimal is the Lexicon? ...
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17
Disambiguatory Signals are Stronger in Word-initial Positions ...
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18
Modeling the Unigram Distribution
In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (2021)
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19
What About the Precedent: An Information-Theoretic Analysis of Common Law
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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20
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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