Communication Sensation Recognition Using Machine Learning Techniques
Mekala. Abigna1, Swapna Sunkara2
1Mekala.Abigna, M.Tech, Department of Computer Science and Engineering, CMR Engineering College, Medchal (Telangana), India.
2Swapna Sunkara, Assistant Professor, Department of Computer Science and Engineering, CMR Engineering College, Medchal (Telangana), India.
Manuscript received on 05 June 2019 | Revised Manuscript received on 30 June 2019 | Manuscript Published on 04 July 2019 | PP: 709-714 | Volume-8 Issue-1S4 June 2019 | Retrieval Number: A11320681S419/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Emotion detection and recognition is an interdisciplinary branch of computing technology, which is used to capture, store, process, and interpret human emotions and generate results for better decision-making in real time. It includes analyzing various emotions through facial expressions, postures, gestures, speech, text, and temperature changes in the human body. All the emotions are captured from special image sensing cameras. The implementation of the system includes training and testing of the speech data. Machine Learning/Deep Learning, Support vector machine methods are used to train or catalog the data to find altered types of emotions. The fields, such as cognitive science, computer science and engineering, and neuroscience, among others, are extensively involved in the development of CSR systems. The implementation of the system includes training and testing of the speech data. Machine Learning/Deep Learning methods are used to train or classify the data to find different types of emotions.
Keywords: Deep Learning, SVM, Machine Learning, MFCS, NN.
Scope of the Article: Machine Learning