Abstract:
Emotion recognition is one of the most difficult jobs in the Natural Language
Processing (NLP) sector since it relies significantly on contextual information and
mixed emotions in a sentence during the emotion detection process. Therefore, we
propose two deep learning approaches CNN and Bi-LSTM, we built these two models
on a dataset that contains six levels of emotions. The two models have proven to give
good accuracy above 90% on this dataset. From that, we have decided to try them out
on thirteen levels of emotions to see if we can still achieve reasonable performance on
a high level of emotions
Description:
Supervised by
Ms. Lutfun Nahar Lota,
Asst. Professor,
Department of Computer Science and Engineering(CSE),
Islamic University of Technology (IUT)
Board Bazar, Gazipur-1704, Bangladesh.
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
