Training a Natural Language Generator From Unaligned Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F15%3A10318129" target="_blank" >RIV/00216208:11320/15:10318129 - isvavai.cz</a>
Result on the web
<a href="https://aclweb.org/anthology/P/P15/P15-1044.pdf" target="_blank" >https://aclweb.org/anthology/P/P15/P15-1044.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Training a Natural Language Generator From Unaligned Data
Original language description
We present a novel syntax-based natural language generation system that is trainable from unaligned pairs of input meaning representations and output sentences. It is divided into sentence planning, which incrementally builds deep-syntactic dependency trees, and surface realization. Sentence planner is based on A* search with a perceptron ranker that uses novel differing subtree updates and a simple future promise estimation; surface realization uses a rule-based pipeline from the Treex NLP toolkit. Ourfirst results show that training from unaligned data is feasible, the outputs of our generator are mostly fluent and relevant.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
ISBN
978-1-941643-72-3
ISSN
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e-ISSN
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Number of pages
11
Pages from-to
451-461
Publisher name
Association for Computational Linguistics
Place of publication
Stroudsburg, PA, USA
Event location
Beijing, China
Event date
Jul 26, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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