• Dheeraj D
• Sushmitha K
• Sahana A.G
• Yashaswini R

Recognition of emotion has been an important research area which may reveal some valuable input for different purposes. People expresses their emotions indirectly or directly through their speech, gestures, facial expressions or writings. Many different sources of information, such as speech, text and visual can be used to analyse emotions. Currently, writings take many forms of social media posts, micro-blogs, news articles, etc., and the content of these posts can be useful resource for text mining to discover and show various aspects, including emotions. Extracting emotions behind these posts is a complicated task. To solve this problem, researchers from different fields are trying to find a sufficient and good way to more precisely detect emotions of human from various sources which includes text and spoken words. In this sense, different techniques based on word and sentences, machine learning, natural language processing methods, etc., have been used to achieve better accuracy.

Emotion Recognition, Machine learning, Feature Extraction, Text Data Set

"Cognitive Approach for Behavioral Analysis of Speech Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.4-9, May 2019, Available :http://www.jetir.org/papers/JETIRCR06002.pdf

"Cognitive Approach for Behavioral Analysis of Speech Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp4-9, May 2019, Available at : http://www.jetir.org/papers/JETIRCR06002.pdf