Vocal Analysis and Sentiment Discernment using AI
Bharati Vidyapeeth's College of Engineering, India
Emails: praveensingh3129@gmail.com; preeti.nagrath@bharatividyapeeth.edup
*Correspondence: praveensingh3129@gmail.com
Abstract
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 is 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, conduct market research, understand customers' experiences, and view 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 recognize and analyze the sentiments of the speaker. Our dataset includes some audio songs sung by some singers and some audio clips of a few actors. We trained CNN and LSTM models to analyze our dataset and predict their accuracy. The ever-growing need for sentiment analysis coincides greatly with the extension of social media such as forum discussions, and social networks like Facebook, Twitter, Instagram, and many other similar platforms.
Keywords: Vocal Analysis; Sentiment Discernment; Artificial Intelligence; Personal development