Language Support¶
Currently rasa NLU is tested and readily available for the following languages:
backend | supported languages |
---|---|
spacy-sklearn | english (en ),
german (de ),
spanish (es ),
portuguese (pt ),
italian (it ),
dutch (nl ),
french (fr ) |
MITIE | english (en ) |
These languages can be set as part of the Configuration.
Adding a new language¶
We want to make the process of adding new languages as simple as possible to increase the number of supported languages. Nevertheless, to use a language you either need a trained word representation or you need to train that presentation on your own using a large corpus of text data in that language.
These are the steps necessary to add a new language:
spacy-sklearn¶
spaCy already provides a really good documentation page about Adding languages. This will help you train a tokenizer and vocabulary for a new language in spaCy.
As described in the documentation, you need to register your language using set_lang_class()
which will
allow rasa NLU to load and use your new language by passing in your language identifier as the language
Configuration option.
MITIE¶
- Get a ~clean language corpus (a Wikipedia dump works) as a set of text files
- Build and run MITIE wordrep tool on your corpus. This can take several hours/days depending on your dataset and your workstation. You’ll need something like 128GB of RAM for wordrep to run - yes that’s alot: try to extend your swap.
- Set the path of your new
total_word_feature_extractor.dat
as value of the mitie_file parameter inconfig_mitie.json