2692-4048ISSN (Online)
2770-0070ISSN (Print)
Volume 7 , Issue 2 , PP: 100-109, 2022 | Cite this article as | XML | Html | PDF | Full Length Article
Praveen Singh 1 * , Preeti Nagrath 2
Doi: https://doi.org/10.54216/FPA.070204
One of the major factors for personal development and growth is understanding human emotions, and therefore it plays an important role in imitating human intelligence. Vocal and Sentiment analysis are the major focus points for advancement in Artificial Intelligence (AI). Sentiment analysis provides major help to data analysts of big enterprises to measure public opinion, conducting market research, understanding customers experience and viewing brand and product reputation. Emotion recognition provides an opportunity to grasp the general people’s sentiments about social events, marketing strategies, political views and product liking. In this paper, we have used various AI models on a variety of audio datasets to recognise and analyse the sentiments of the speaker. Our dataset includes some audio songs sung by some singers and some audio clips of few actors. We trained CNN and LSTM models to analyse our dataset and predict their accuracy. The ever-growing need of sentiment analysis coincides greatly with the extension of social media such as forum discussions, social networks like Facebook, Twitter, Instagram and many other similar platforms.
Vocal Analysis , Sentiment Discernment , Artificial Intelligence , Personal development
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