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1
Inducing Language-Agnostic Multilingual Representations ...
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2
Zero-Shot Cross-Lingual Transfer with Meta Learning ...
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3
SIGTYP 2020 Shared Task: Prediction of Typological Features ...
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4
Uncovering Probabilistic Implications in Typological Knowledge Bases ...
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5
Back to the Future -- Sequential Alignment of Text Representations ...
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6
What do Language Representations Really Represent? ...
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7
What Do Language Representations Really Represent?
In: Bjerva, Johannes; Östling, Robert; Veiga, Maria Han; Tiedemann, Jörg; Augenstein, Isabelle (2019). What Do Language Representations Really Represent? Computational Linguistics, 45(2):381-389. (2019)
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8
Copenhagen at CoNLL--SIGMORPHON 2018: Multilingual Inflection in Context with Explicit Morphosyntactic Decoding ...
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9
Parameter sharing between dependency parsers for related languages ...
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10
Multitask and Multilingual Modelling for Lexical Analysis ...
Bjerva, Johannes. - : arXiv, 2018
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11
From Phonology to Syntax: Unsupervised Linguistic Typology at Different Levels with Language Embeddings ...
Abstract: A core part of linguistic typology is the classification of languages according to linguistic properties, such as those detailed in the World Atlas of Language Structure (WALS). Doing this manually is prohibitively time-consuming, which is in part evidenced by the fact that only 100 out of over 7,000 languages spoken in the world are fully covered in WALS. We learn distributed language representations, which can be used to predict typological properties on a massively multilingual scale. Additionally, quantitative and qualitative analyses of these language embeddings can tell us how language similarities are encoded in NLP models for tasks at different typological levels. The representations are learned in an unsupervised manner alongside tasks at three typological levels: phonology (grapheme-to-phoneme prediction, and phoneme reconstruction), morphology (morphological inflection), and syntax (part-of-speech tagging). We consider more than 800 languages and find significant differences in the language ... : Accepted to NAACL 2018 (long paper). arXiv admin note: text overlap with arXiv:1711.05468 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/1802.09375
https://dx.doi.org/10.48550/arxiv.1802.09375
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12
The Parallel Meaning Bank: Towards a Multilingual Corpus of Translations Annotated with Compositional Meaning Representations
In: 15th Conference of the European Chapter of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-01630960 ; 15th Conference of the European Chapter of the Association for Computational Linguistics, Apr 2017, Valencia, Spain. pp.242 - 247 (2017)
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13
Tracking Typological Traits of Uralic Languages in Distributed Language Representations ...
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14
Articulation rate in Swedish child-directed speech increases as a function of the age of the child even when surprisal is controlled for ...
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15
One Model to Rule them all: Multitask and Multilingual Modelling for Lexical Analysis ...
Bjerva, Johannes. - : arXiv, 2017
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16
The Parallel Meaning Bank: Towards a Multilingual Corpus of Translations Annotated with Compositional Meaning Representations ...
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17
Rethinking intertextuality through a word-space and social network approach – the case of Cassiodorus
In: https://hal.archives-ouvertes.fr/hal-01279833 ; 2016 (2016)
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18
Semantic Tagging with Deep Residual Networks ...
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