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SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ...
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83 |
SIGTYP 2020 Shared Task: Prediction of Typological Features ...
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The Paradigm Discovery Problem ...
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Abstract:
This work treats the paradigm discovery problem (PDP), the task of learning an inflectional morphological system from unannotated sentences. We formalize the PDP and develop evaluation metrics for judging systems. Using currently available resources, we construct datasets for the task. We also devise a heuristic benchmark for the PDP and report empirical results on five diverse languages. Our benchmark system first makes use of word embeddings and string similarity to cluster forms by cell and by paradigm. Then, we bootstrap a neural transducer on top of the clustered data to predict words to realize the empty paradigm slots. An error analysis of our system suggests clustering by cell across different inflection classes is the most pressing challenge for future work. ... : Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics ...
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URL: https://dx.doi.org/10.3929/ethz-b-000462310 http://hdl.handle.net/20.500.11850/462310
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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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89 |
Generalized Entropy Regularization or: There’s Nothing Special about Label Smoothing ...
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94 |
Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model ...
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Please Mind the Root: Decoding Arborescences for Dependency Parsing
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In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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Measuring the Similarity of Grammatical Gender Systems by Comparing Partitions
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In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model
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In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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