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1
Speakers Enhance Contextually Confusable Words
Meinhardt, Eric; Bakovic, Eric; Bergen, Leon. - : eScholarship, University of California, 2020
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2
Predicting Declension Class from Form and Meaning
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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3
The Paradigm Discovery Problem
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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4
A Tale of a Probe and a Parser
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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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)
Abstract: A major hurdle in data-driven research on typology is having sufficient data in many languages to draw meaningful conclusions. We present VoxClamantis V1.0, the first large-scale corpus for phonetic typology, with aligned segments and estimated phoneme-level labels in 690 readings spanning 635 languages, along with acoustic-phonetic measures of vowels and sibilants. Access to such data can greatly facilitate investigation of phonetic typology at a large scale and across many languages. However, it is non-trivial and computationally intensive to obtain such alignments for hundreds of languages, many of which have few to no resources presently available. We describe the methodology to create our corpus, discuss caveats with current methods and their impact on the utility of this data, and illustrate possible research directions through a series of case studies on the 48 highest-quality readings. Our corpus and scripts are publicly available for non-commercial use at https://voxclamantisproject.github.io.
URL: https://doi.org/10.3929/ethz-b-000446011
https://hdl.handle.net/20.500.11850/446011
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6
Information-Theoretic Probing for Linguistic Structure
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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7
It’s Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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8
ASSET: A dataset for tuning and evaluation of sentence simplification models with multiple rewriting transformations
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9
Non-linear instance-based cross-lingual mapping for non-isomorphic embedding spaces
Glavaš, Goran; Vulić, Ivan. - : Association for Computational Linguistics, 2020
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10
Classification-based self-learning for weakly supervised bilingual lexicon induction
Vulić, Ivan; Korhonen, Anna; Glavaš, Goran. - : Association for Computational Linguistics, 2020
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11
On the limitations of cross-lingual encoders as exposed by reference-free machine translation evaluation
Zhao, Wei; Glavaš, Goran; Peyrard, Maxime. - : Association for Computational Linguistics, 2020
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