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Hits 321 – 339 of 339

321
Applying N-gram Alignment Entropy to Improve Feature Decay Algorithms
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 245-256 (2017) (2017)
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322
Comparative Human and Automatic Evaluation of Glass-Box and Black-Box Approaches to Interactive Translation Prediction
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 97-108 (2017) (2017)
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323
Historical Documents Modernization
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 295-306 (2017) (2017)
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324
Maintaining Sentiment Polarity in Translation of User-Generated Content
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 73-84 (2017) (2017)
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325
Is Neural Machine Translation the New State of the Art?
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 109-120 (2017) (2017)
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326
Linguistically Motivated Vocabulary Reduction for Neural Machine Translation from Turkish to English
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 331-342 (2017) (2017)
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327
Learning Morphological Normalization for Translation from and into Morphologically Rich Languages
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 49-60 (2017) (2017)
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328
Continuous Learning from Human Post-Edits for Neural Machine Translation
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 233-244 (2017) (2017)
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329
Fine-Grained Human Evaluation of Neural Versus Phrase-Based Machine Translation
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 121-132 (2017) (2017)
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330
A Neural Network Architecture for Detecting Grammatical Errors in Statistical Machine Translation
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 133-145 (2017) (2017)
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331
A Linguistic Evaluation of Rule-Based, Phrase-Based, and Neural MT Engines
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 159-170 (2017) (2017)
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332
Neural Networks Classifier for Data Selection in Statistical Machine Translation
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 283-294 (2017) (2017)
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333
Empirical Investigation of Optimization Algorithms in Neural Machine Translation
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 13-25 (2017) (2017)
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334
Parallelization of Neural Network Training for NLP with Hogwild!
In: Prague Bulletin of Mathematical Linguistics , Vol 109, Iss 1, Pp 29-38 (2017) (2017)
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335
Neural Monkey: An Open-source Tool for Sequence Learning
In: Prague Bulletin of Mathematical Linguistics , Vol 107, Iss 1, Pp 5-17 (2017) (2017)
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336
Difference between Written and Spoken Czech: The Case of Verbal Nouns Denoting an Action
In: Prague Bulletin of Mathematical Linguistics , Vol 107, Iss 1, Pp 19-38 (2017) (2017)
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337
Comparative Quality Estimation for Machine Translation Observations on Machine Learning and Features
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 307-318 (2017) (2017)
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338
Learnability and falsifiability of Construction Grammars
In: Proceedings of the Linguistic Society of America; Vol 2 (2017): Proceedings of the Linguistic Society of America; 1:1–15 ; 2473-8689 (2017)
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339
Variation in the pronunciation/silence of the prepositions in locative determiners
In: Proceedings of the Linguistic Society of America; Vol 2 (2017): Proceedings of the Linguistic Society of America; 22:1–15 ; 2473-8689 (2017)
Abstract: We argue that the micro-variation observed in the pronunciation/silence of the prepositional head of locative determiners in Fallese, a dialect spoken in Abruzzi, follows from the option of valuing features by either External Merge or by Internal Merge, given Spell-Out conditions, whereas this option is not available in English and Italian. It follows that the prepositional head is silent in Italian and English, whereas it can be pronounced in Fallese when the Specifier of the locative determiner is not filled. We show that this feature-based approach to micro-variation, in conjunction with principles of efficient computation, makes correct predictions for the pronunciation of the prepositional head in other functional categories, as well as it makes predictions on the diachronic development of locative determiners Latin to Fallese and from Latin to Italian, otherwise it looks like Fallese is an old stage of Italian.
Keyword: Biolinguistics; Computational Linguistics; language variation; locative determiners; merge; Morphology; prepositions; pronunciation; Syntax; third factor principles
URL: http://journals.linguisticsociety.org/proceedings/index.php/PLSA/article/view/4072
https://doi.org/10.3765/plsa.v2i0.4072
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