  In recent times, we have seen an increased use of text chat for communication
on social networks and smartphones. This particularly involves the use of
Hindi-English code-mixed text which contains words which are not recognized in
English vocabulary. We have worked on detecting emotions in these mixed data
and classify the sentences in human emotions which are angry, fear, happy or
sad. We have used state of the art natural language processing models and
compared their performance on the dataset comprising sentences in this mixed
data. The dataset was collected and annotated from sources and then used to
train the models.
