Hi, I am pretty new in Moses SMT and in the field of NLP. I've successfully trained two translators for Bikol (ISO 639-3 bcl <http://www-01.sil.org/iso639-3/documentation.asp?id=bcl>) to English and an English to Bikol. Evaluation for both translators resulted to decent BLEU scores which is around 33.0 with parameters (ie. -mbr -mp -s) but without additional pre-processing techniques like (POS tagging, morphological analysis, etc...). And my questions are:
1. Does training an Unsupervised Transliteration Model could help to improve the translation quality involving a language (Bikol) that consist of alphanumeric characters only? 2. What are the other pre-processing techniques that does not require a lexicon (Dictionary)? I am having difficulties to find a good source of Bikol lexicons because of its unpopularity. 3. Is it possible to train a translation model with a POS tagged corpus as a source language to a target language which corpus is not POS tagged or vice versa? Thank you. :)
_______________________________________________ Moses-support mailing list [email protected] http://mailman.mit.edu/mailman/listinfo/moses-support
