Sentiment Analysis on Voice data using Deep Learning

Registration ID: IJNRD_181048

Published ID: IJNRD2204094

: http://doi.one/10.1729/Journal.29980

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DEEPA YOGISH, Asha N, Yogish H k, Abhishek K

Deep learning, Machine learning, MFCC, Convolution Neural Network, classifications, RAVDESS, TESS, Emotion detection

Sentiment Analysis (SA) is an application of Natural Language Processing (NLP) that is used to identify and extract sensitive information, such as a person's perspective on a particular piece of text. SA's main idea is to divide the authors' ideas on a variety of topics into positive, negative, or neutral categories. It works in a variety of domains including Business Intelligence (BI), politics, social science, etc. In recent years we have seen an increase in social networking websites, microblogs, and Web applications with a significant increase in user-generated data for sentiment mining. Data from online posts, tweets, videos, etc., all specific reviews on diverse subjects and events, provide big possibilities to have a look at and examine human opinions and sentiment. In this paper, we study how the sentiment of a voice data of a human can be classified into sentiment i.e., emotions possessed by the user while speaking. Emotions divided by the model are neutral, calm, happy, sad, angry, nervous, disgusted, and surprised. Our model captured and analyzed users' emotions and used them to improve user interaction / experience. The models for emotional recognition suggested here are based on the Deep Learning (DL) and Convolution Neural Networks (CNN). The main idea is to consider the Mel-Frequency Cepstral Coefficients (MFCC) normally referred to as the "spectrum of a spectrum", to be the only feature used for training the model.

Published Paper   E-Certificate

DEEPA YOGISH, Asha N, Yogish H k, & Abhishek K (April-2022). Sentiment Analysis on Voice data using Deep Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(4), 778-782. http://doi.one/10.1729/Journal.29980

Volume 7 Issue 4, April-2022

Pages : 778-782

Paper Reg. ID: IJNRD_181048

Published Paper Id: IJNRD2204094

Research Area: Engineering

Author Type: Indian Author

Country: BANGALORE, KARNATAKA, INDIA

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Crossref DOI: http://doi.one/10.1729/Journal.29980

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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