training skip-grams on synthetic code-mixed text generated through linguistic models of
code-mixing, on two tasks-sentiment analysis and POS tagging for code-mixed text. Our
results show that while CVM and CCA based embeddings perform as well as the proposed
embedding technique on semantic and syntactic tasks respectively, the proposed approach
provides the best performance for both tasks overall. Thus, this study demonstrates that …