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.