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Hits 81 – 100 of 163

81
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ...
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Intrinsic Probing through Dimension Selection ...
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83
SIGTYP 2020 Shared Task: Prediction of Typological Features ...
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84
The Paradigm Discovery Problem ...
Erdmann, Alexander; Elsner, Micha; Wu, Shijie. - : ETH Zurich, 2020
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85
Information-Theoretic Probing for Linguistic Structure ...
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86
It’s Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information ...
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87
Information-Theoretic Probing for Linguistic Structure ...
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88
Intrinsic Probing through Dimension Selection ...
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89
Generalized Entropy Regularization or: There’s Nothing Special about Label Smoothing ...
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90
A Corpus for Large-Scale Phonetic Typology ...
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91
Phonotactic Complexity and its Trade-offs ...
Abstract: We present methods for calculating a measure of phonotactic complexity---bits per phoneme---that permits a straightforward cross-linguistic comparison. When given a word, represented as a sequence of phonemic segments such as symbols in the international phonetic alphabet, and a statistical model trained on a sample of word types from the language, we can approximately measure bits per phoneme using the negative log-probability of that word under the model. This simple measure allows us to compare the entropy across languages, giving insight into how complex a language's phonotactics are. Using a collection of 1016 basic concept words across 106 languages, we demonstrate a very strong negative correlation of -0.74 between bits per phoneme and the average length of words. ... : Published in TACL: https://doi.org/10.1162/tacl_a_00296 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2005.03774
https://dx.doi.org/10.48550/arxiv.2005.03774
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92
Phonotactic Complexity and Its Trade-offs ...
Pimentel, Tiago; Roark, Brian; Cotterell, Ryan. - : ETH Zurich, 2020
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93
A Corpus for Large-Scale Phonetic Typology ...
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94
Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model ...
Leung, Jun Yen; Emerson, Guy; Cotterell, Ryan. - : ETH Zurich, 2020
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95
Morphologically Aware Word-Level Translation ...
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96
Predicting Declension Class from Form and Meaning ...
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97
Predicting declension class from form and meaning
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98
Please Mind the Root: Decoding Arborescences for Dependency Parsing
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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99
Measuring the Similarity of Grammatical Gender Systems by Comparing Partitions
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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100
Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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