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NNBlocks: A Deep Learning Framework for Computational Linguistics Neural Network Models

Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)

DOI:10.63317/3agk4gx5zjig

Abstract

Lately, with the success of Deep Learning techniques in some computational linguistics tasks, many researchers want to explore new models for their linguistics applications. These models tend to be very different from what standard Neural Networks look like, limiting the possibility to use standard Neural Networks frameworks. This work presents NNBlocks, a new framework written in Python to build and train Neural Networks that are not constrained by a specific kind of architecture, making it possible to use it in computational linguistics.

Details

Paper ID
lrec2016-main-330
Pages
pp. 2081-2085
BibKey
caroli-etal-2016-nnblocks
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
978-2-9517408-9-1
Conference
Tenth International Conference on Language Resources and Evaluation
Location
Portorož, Slovenia
Date
23 May 2016 28 May 2016

Authors

  • FC

    Frederico Tommasi Caroli

  • AF

    André Freitas

  • Jd

    João Carlos Pereira da Silva

  • SH

    Siegfried Handschuh

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