Speech Emotion detection using Machine Learning

Speech Emotion detection using Machine Learning
Author(s):
Sanskruti Gaikwad, Prerana Patil, Pritesh Gadiya, Vyankaesh Khetri , PROF. DR. MRS. SARITA DESHPANDE
Keywords:
Detection, Speech Input, Feature Extraction
Abstract
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 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, their 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 (ANNs) that are used to distinguish emotions such as anger, disgust, fear, happiness, neutrality, sadness, and surprise.
Article Details
Unique Paper ID: 163260 Publication Volume & Issue: Volume 10, Issue 11 Page(s): 826 - 830
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