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Found 13 papers, 10 papers with code
Online Learning for Effort Reduction in Interactive Neural Machine Translation
We show that a neural machine translation system can be rapidly adapted to a specific domain, exclusively by means of online learning techniques.
Online Learning for Neural Machine Translation Post-editing
Neural machine translation has meant a revolution of the field.
NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning
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.
Active Learning for Interactive Neural Machine Translation of Data Streams
We study the application of active learning techniques to the translation of unbounded data streams via interactive neural machine translation.
Video Description using Bidirectional Recurrent Neural Networks
Although traditionally used in the machine translation field, the encoder-decoder framework has been recently applied for the generation of video and image descriptions.
A Neural, Interactive-predictive System for Multimodal Sequence to Sequence Tasks
We present a demonstration of a neural interactive-predictive system for tackling multimodal sequence to sequence tasks.
Egocentric Video Description based on Temporally-Linked Sequences
We propose a novel methodology that exploits information from temporally neighboring events, matching precisely the nature of egocentric sequences.
VIBIKNet: Visual Bidirectional Kernelized Network for Visual Question Answering
In this paper, we address the problem of visual question answering by proposing a novel model, called VIBIKNet.
Neural Networks Classifier for Data Selection in Statistical Machine Translation
We address the data selection problem in statistical machine translation (SMT) as a classification task.
Demonstration of a Neural Machine Translation System with Online Learning for Translators
We introduce a demonstration of our system, which implements online learning for neural machine translation in a production environment.
Interactive-predictive neural multimodal systems
We show that, following this framework, we approximately halve the effort spent for correcting the outputs generated by the automatic systems.
Incremental Adaptation of NMT for Professional Post-editors: A User Study
A common use of machine translation in the industry is providing initial translation hypotheses, which are later supervised and post-edited by a human expert.
A User Study of the Incremental Learning in NMT
Adaptive neural machine translation systems, able to incrementally update the underlying models under an online learning regime, have been proven to be useful to improve the efficiency of this workflow.
