Syntactic and Semantic Features For Code-Switching Factored Language Models
TABLE III: PPL of FLMs with POS tags and LID
['Model', 'PPL dev', 'PPL eval']
First, the factor POS tag is explored. A language model containing the last word and the two last POS tags as conditioning factors is trained. This choice of conditioning factors is obtained by the genetic algorithm and maintained during the manual optimization. Second, a language model using only language identifiers (LID) and words as features is trained. Finally, the factors words, POS tags and language information are combined. The perplexity results show that they provide complementary information which helps to improve the language model predictions.