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21
Continuous multilinguality with language vectors ...
Abstract: Most existing models for multilingual natural language processing (NLP) treat language as a discrete category, and make predictions for either one language or the other. In contrast, we propose using continuous vector representations of language. We show that these can be learned efficiently with a character-based neural language model, and used to improve inference about language varieties not seen during training. In experiments with 1303 Bible translations into 990 different languages, we empirically explore the capacity of multilingual language models, and also show that the language vectors capture genetic relationships between languages. ... : In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics (EACL), Valencia, Spain, April, 2017 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/1612.07486
https://dx.doi.org/10.48550/arxiv.1612.07486
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22
Inferring the location of authors from words in their texts ...
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23
Efficient Word Alignment with Markov Chain Monte Carlo
In: Prague Bulletin of Mathematical Linguistics , Vol 106, Iss 1, Pp 125-146 (2016) (2016)
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24
Inferring the location of authors from words in their texts
Parkvall, Mikael; Bergren, Max; Karlgren, Jussi. - : KTH, Teoretisk datalogi, TCS, 2015. : Gavagai, 2015. : Stockholms universitet, 2015
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