A Hybrid Approach for Amazigh-English Machine Translation

Abstract

In this paper, we present our hybrid methodology for building a bidirectional Amazigh-English machine translation. The architecture of the proposed system is based on both Interlingua-Based Machine Translation (IBMT) and Statistical-Based Machine Translation (SBMT) approaches. Amazigh is a less-resourced language. It does not have parallel corpora with enough size. So, using statistical approach for such language will not be a good choice, because this approach requires large parallel corpora to well train probabilistic models, and to ensure a translation of good quality. Since we dispose of an Amazigh IBMT based deconverter, we thought, firstly, to use it in building an Amazigh-English parallel corpus. This latter have been exploited to train the necessary models in SBMT.