NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning

July 09, 2018 ยท Declared Dead ยท ๐Ÿ› Prague Bulletin of Mathematical Linguistics

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Authors รlvaro Peris, Francisco Casacuberta arXiv ID 1807.03096 Category cs.CL: Computation & Language Citations 21 Venue Prague Bulletin of Mathematical Linguistics Last Checked 4 months ago
Abstract
We present NMT-Keras, a flexible toolkit for training deep learning models, which puts a particular emphasis on the development of advanced applications of neural machine translation systems, such as interactive-predictive translation protocols and long-term adaptation of the translation system via continuous learning. NMT-Keras is based on an extended version of the popular Keras library, and it runs on Theano and Tensorflow. State-of-the-art neural machine translation models are deployed and used following the high-level framework provided by Keras. Given its high modularity and flexibility, it also has been extended to tackle different problems, such as image and video captioning, sentence classification and visual question answering.
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