Dear James and Moses devs, I guess everyone's hunch would be whether you've done tuning correctly before the awkward results you've reported.
---- Read on for sob story about me and moses and some guide to sooth the tone, try i may. Please skip/delete, if you would not like to read the sob story =) I am not an expert in moses nor someone who have used it extensively. But I can clearly say that the Moses learning curve is steeper than most NLP/MT libraries. Still it is worth going through the rite of passage, from step 1-9: http://www.statmt.org/moses/?n=FactoredTraining.PrepareData . Beyond that there is a zoo of other considerations such as tuning, decoding tricks, other translation model training and more recently how language model is trained. However to say that there is a major bug in moses just because you aren't getting the desired result is an ungrounded statement. There are many others who have achieved results before you, just because you can't do it means it's broken. It took me close to 2 years to understand some bits of how SMT works and even smaller bit of how moses work. My best learning experience came from participating in WMT shared task and competing against other researchers. At best, I learnt how to use moses after doing that. The only time I start to understand a little SMT is when I'm forced to grind through the Philip Koehn's book and try reimplementing a super simplistic unrealistic decoder while talking to the moses devs at MT Marathon. Still there's much for me to learn. Possibly, linking these resources to the moses page might help sooth the pains of getting to know moses: - *Tutorials:* - *TAUS tutoral*: https://translate.taus.net/translate/mosescore/machine-translation-and-moses-tutorial#getting-started - http://www.idiap.ch/~apbelis/hlt-course/TP-MT-instructions.pdf - http://www.cs.upc.edu/~cristinae/CV/docs/tutorialSMTprint.pdf - http://nlp.cs.upc.edu/lrec-mttutorial/# - *MT Marathon slides*, e.g. http://statmt.org/mtm14/index.php?n=Main.TalksLecturesLabs , http://www.statmt.org/mtma15/index.php?n=Main.Program - *Baseline systems for other sources:* - *WAT*: http://orchid.kuee.kyoto-u.ac.jp/WAT/baseline/baselineSystems.html - *Friends of Moses*: - http://www.cdec-decoder.org/ , - https://kheafield.com/code/kenlm/ , - http://joshua-decoder.org/ , - http://www-nlp.stanford.edu/wiki/Software/Phrasal2 - http://stp.lingfil.uu.se/~ch/docent-lab.html , etc. Even if the above isn't on the official moses site, would I have the "blessings of the moses dev" to put them up on Wikipedia https://en.wikipedia.org/wiki/Moses_(machine_translation)? Sadly, it's my last year of my PhD journey and I'm finalizing my experiments albeit knowing little of SMT and moses. But I would still like to either port some of the moses code to python or write wrappers for NLTK to call moses. BTW, for now, these are valid lines in NLTK: >>> import nltk >>> nltk.download('moses_sample') The Moses developers have done a great job in open-sourcing one of the first SMT device that have spun off others and they're at doing it. @James, if you ask politely, usually some nice devs will guide you to the right answer(s). Regards, Liling
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