We learn this group of multinomial parameters, θ for each language, in an unsupervised fashion, and in doing so, adapt to the proportions of languages found in the particular input document.
using our parameterization, the probability of transitioning from language to , given previous character e, is:   Finally, because our code-switching LM uses multiple separate language-specific n-gram models P CHAR , we are able to maintain a distinct set of valid characters for each language.