Text-to-text machine translation using the RECONTRA connectionist model

被引：0
|
作者：
Castaño, MA
Casacuberta, F
机构：
[1] Univ Jaume 1 Castellon, Dept Informat, Castellon de La Plana, Spain
[2] Univ Politecn Valencia, Dept Sistemas Informat & Computac, E-46071 Valencia, Spain
来源：
ENGINEERING APPLICATIONS OF BIO-INSPIRED ARTIFICIAL NEURAL NETWORKS, VOL II | 1999年 / 1607卷
关键词：
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Encouragingly accurate translations have recently been obtained using a connectionist translator called RECONTRA (Recurrent Connectionist Translator). In contrast to traditional Knowledge-Based systems, this model is built from training data resulting in an Example-Based approach. It directly carries out the translation between the source and target language and employs a simple (recurrent) connectionist topology and a simple training scheme. This paper extends previous work exploring the capabilities of this RECONTRA model to perform text-to-text translations in limited-domain tasks.
引用
收藏
页码：683 / 692
页数：10
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