Paper Title
Emotion Recognition Using Text with Emojis and Speech

Abstract
Emotion Recognition can enhance the competencies of social media platforms and other tech companies, as the need for grasping the user's attention towards them has increased tremendously. This paper concentrates on recognising user emotion through text-only, text with emojis, and speech. A hybrid model is designed with the combination of RoBERTa- LSTM-CNN models, which outperforms the individual models. Speech Emotion Recognition involves extracting the features of an audio file irrespective of the semantic contents. MFCC-CNN is used to analyse the audio features based on various augmented audio segments, and speech-to-text transcription is used to increase the accuracy of the prediction. Based on the detected emotion, content is recommended through music and videos to enhance the user's mood. Feedback taken from users is stored in the database to improve future predictions. Keywords - MFCC, CNN, Bi-LSTM, BERT, RoBERTa, Word Embedding.

Author - Dheeraj S Reddy, Mehul Bhandari, Mahesh Kumawat, Ashwini M Joshi, Rohith Kumar R

Published : Volume-10,Issue-6  ( Jun, 2023 )

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