Paper Title
Vocal Vibes Speech Emotion Recognition using Machine Learning
Article Identifiers
Registration ID: IJNRD_217234
Published ID: IJNRD2404046
: http://doi.one/10.1729/Journal.38730
Keywords
Emotion , Machine Learning , Speech
Abstract
One of the quickest and most natural ways for humans to communicate is through speech. Speech emotion recognition is the process of accurately anticipating a human's emotion from their speech. It improves the way people and computers communicate. Although it is tricky to annotate audio and difficult to forecast a person's sentiment because emotions are subjective, "Speech Emotion Recognition (SER)" makes this possible. Various researchers have created a variety of systems to extract the emotions from the speech stream. Speech qualities in particular are more helpful in identifying between various emotions, and if they are unclear, this is the cause of how challenging it is to identify an emotion from a speaker's speech. A variety of the datasets for speech emotions, its modelling, and types are accessible, and they aid in determining the style of speech. After feature extraction, the classification of speech emotions is a crucial component, so in this system proposal, we introduced Artificial Neural Networks (ANN model) that are utilised to distinguish emotions such as angry, disgust, Fear, happy, neutral, Sad and surprise. The proposed system model Artificial Neural Networks (ANN model) achieved training accuracy of 100% and Validation accuracy of 99%.
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How To Cite (APA)
Sanskruti Gaikwad, Prerana Patil, Pritesh Gadiya, & Vyankatesh Khetri (April-2024). Vocal Vibes Speech Emotion Recognition using Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), a354-a357. http://doi.one/10.1729/Journal.38730
Issue
Volume 9 Issue 4, April-2024
Pages : a354-a357
Other Publication Details
Paper Reg. ID: IJNRD_217234
Published Paper Id: IJNRD2404046
Downloads: 000122021
Research Area: Engineering
Author Type: Indian Author
Country: Baner , Pune, Maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2404046.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404046
Crossref DOI: http://doi.one/10.1729/Journal.38730
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