@inproceedings{lee2018accumulating,
author = {Lee, Sungjin},
title = {Accumulating Conversational Skills using Continual Learning},
booktitle = {IEEE SLT 2018},
year = {2018},
month = {September},
abstract = {While neural conversational models have led to promising advances in reducing hand-crafted features and errors induced by the traditional complex system architecture, training neural models from scratch requires an enormous amount of data. If pre-trained models can be reused when they have many things in common with a new task, we can significantly cut down the amount of required data. To achieve this goal, we adopt a neural continual learning algorithm to allow a conversational agent to accumulate skills across different tasks in a data-efficient way.},
url = {http://approjects.co.za/?big=en-us/research/publication/accumulating-conversational-skills-using-continual-learning/},
}