An Analysis of Subtask-Dependency in Robot Command Interpretation with Dilated CNNs
Proceedings of the 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018),
pages 25--30,
- Apr 2018
In this paper, we tackle sequence-to-tree transduction for
language processing with neural networks implementing several subtasks,
namely tokenization, semantic annotation, and tree generation. Our research question is how the individual subtasks influence the overall end-toend learning performance in case of a convolutional network with dilated
perceptive fields. We investigate a benchmark problem for robot command
interpretation and conclude that dilation has a strong positive effect for
performing character-level transduction and for generating parsing trees.
@InProceedings{EAAW18,
author = {Eppe, Manfred and Alpay, Tayfun and Abawi, Fares and Wermter, Stefan},
title = {An Analysis of Subtask-Dependency in Robot Command Interpretation with Dilated CNNs},
booktitle = {Proceedings of the 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018)},
journal = {None},
editors = {}
number = {}
volume = {}
pages = {25--30},
year = {2018},
month = {Apr},
publisher = {None},
doi = {}
}