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2008
IEEE

Neural Network Language Models for Translation with Limited Data

9 years 6 months ago
Neural Network Language Models for Translation with Limited Data
In this paper we present how to estimate a continuous space Language Model with a Neural Network to be used in a Statistical Machine Translation system. We report results for an Italian-English translation task obtained on a small corpus (about 150 K tokens), that can be considered a task with a lack of training data. Different word history length included in the connectionist language model (n-gram order) and distinct continuous space representation (i.e. words appearing in the training corpus more than k times) are considered in the study. The experimental results are evaluated by means of automatic evaluation metrics correlated with fluency and adequacy of the generated translations.
Maxim Khalilov, José A. R. Fonollosa, Franc
Added 31 May 2010
Updated 31 May 2010
Type Conference
Year 2008
Where ICTAI
Authors Maxim Khalilov, José A. R. Fonollosa, Francisco Zamora-Martínez, María José Castro Bleda, Salvador España Boquera
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