In this paper we describe a prototype of a Venetan to English
translation system developed under the STILVEN project financed by the Regional
Authorities of Veneto Region in Italy. The general approach is a
statistical one with some preprocessing operations both at training and
translation time (ortographic normalization and POS tagging to make
use of factored models) which are needed especially to overcome two
main problems: the scarcity of Venetan resources (our Venetan-English
corpus is made up of only 13,000 sentences, amounting to 128,000 Venetan
tokens excluding punctuation) and the diasystemic nature of Venetan,
which really represents an ensemble of varieties rather than a single
dialect. We will present in detail the problems related to Venetan, our
ideas to solve them, their implementation and the results obtained so
far