spaCy-CLD: Bringing simple language detection to spaCy

This package is a spaCy 2.0 extension that adds language detection to spaCy's text processing pipeline. Inspired from a discussion here.

Installation

pip install spacy_cld

Usage

Adding the spaCy-CLD component to the processing pipeline is relatively simple:

import spacy
from spacy_cld import LanguageDetector

nlp = spacy.load('en')
language_detector = LanguageDetector()
nlp.add_pipe(language_detector)
doc = nlp('This is some English text.')

doc._.languages  # ['en']
doc._.language_scores['en']  # 0.96

spaCy-CLD operates on Doc and Span spaCy objects. When called on a Doc or Span, the object is given two attributes: languages (a list of up to 3 language codes) and language_scores (a dictionary mapping language codes to confidence scores between 0 and 1).

Under the hood

spacy-cld is a little extension that wraps the PYCLD2 Python library, which in turn wraps the Compact Language Detector 2 C library originally built at Google for the Chromium project. CLD2 uses character n-grams as features and a Naive Bayes classifier to identify 80+ languages from Unicode text strings (or XML/HTML). It can detect up to 3 different languages in a given document, and reports a confidence score (reported in with each language.

For additional details, see the linked project pages for PYCLD2 and CLD2.