  This paper describes our contribution to the SemEval-2020 Task 9 on Sentiment
Analysis for Code-mixed Social Media Text. We investigated two approaches to
solve the task of Hinglish sentiment analysis. The first approach uses
cross-lingual embeddings resulting from projecting Hinglish and pre-trained
English FastText word embeddings in the same space. The second approach
incorporates pre-trained English embeddings that are incrementally retrained
with a set of Hinglish tweets. The results show that the second approach
performs best, with an F1-score of 70.52% on the held-out test data.
