Language Recognition

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In natural language processing, language identification or language guessing is the problem of determining which natural language given content is in. Computational approaches to this problem view it as a special case of text categorization, solved with various statistical methods.

In order to extract the language you'll need to have you document saved on your computer.

After you've installed the Lettria package on Python you'll need to import the library

**import lettria**

Next you are going to need to include your personal API key which can be found

via the Lettria platform in the dashboard.

api_key = 'your personal API key'
nlp = lettria.NLP(api_key)

Now you will need to open your saved document. Be sure to add the name of

‘your file’ since it may differ from the name of my example file.

with open("example.txt", "r") as f:
	example_data = f.readlines()

Next I am going to add the document to the NLP and then print the results.

nlp.add_document(example_data)

In order to extract the language of your document add the following command and run your code.

print([s.language for s in nlp.sentences])

In order to save your results you can use the following command

nlp.save_results('example_results')

And a json file with you results that can be used for further analysis will be saved.

import lettria

api_key = 'your personal API key'
nlp = lettria.NLP(api_key)

with open("example.txt", "r") as f:
	example_data = f.readlines()

nlp.add_document(example_data)
print([s.language for s in nlp.sentences])

nlp.save_results('example_results')