ML Based Approach for Speech Emotion Recognition

ML Based Approach for Speech Emotion Recognition

Prof. Ayesha A. Sayyad, Vishal Surya, Mahesh Chavhan, Subhash Lavand, Chaitanya Kisave

Abstract –The investigation of human discourse is a difficult examination territory as it concerns the discovery of user networks. Feelings assume an underlying part in human communication. The capacity to comprehend human feelings by breaking down voice is alluring in various uses of discourse acknowledgment in feelings can be found in various zones, for example, the association among PCs and people and call focuses. Already, feeling acknowledgment utilized straightforward classifiers on bag- of-words models. Nonetheless, the current work of feeling acknowledgment on Voice was done with the assistance of profound learning strategies on static voice information. The proposed strategy centers around expanding the general precision of feeling acknowledgment during calls utilizing man-made consciousness. The general point is to precisely perceive the different feelings that a specific speech communicates semantically.

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Keywords- Human Emotion, feature extraction, machine learning, Speech conversion.