An Appraisal on Speech and Emotion Recognition Technologies based on Machine Learning
C Andy Jason1, Sandeep Kumar2
1Sandeep Kumar*, Professor, Sreyas Institute of Engineering and Technology, Hyderabad, India.
2C. Andy Jason, M.Tech Student, Sreyas Institute of Engineering and Technology, Hyderabad, India.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 2266-2276 | Volume-8 Issue-5, January 2020. | Retrieval Number: E5715018520/2020©BEIESP | DOI: 10.35940/ijrte.E5715.018520
Open Access | Ethics and Policies | Cite | Mendeley
© 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: In earlier days, people used speech as a means of communication or the way a listener is conveyed by voice or expression. But the idea of machine learning and various methods are necessary for the recognition of speech in the matter of interaction with machines. With a voice as a bio-metric through use and significance, speech has become an important part of speech development. In this article, we attempted to explain a variety of speech and emotion recognition techniques and comparisons between several methods based on existing algorithms and mostly speech-based methods. We have listed and distinguished speaking technologies that are focused on specifications, databases, classification, feature extraction, enhancement, segmentation and process of Speech Emotion recognition in this paper.
Keywords: Speech Emotion Recognition, Speech Processing, Biometric, Machine Learning, MLP..
Scope of the Article: Machine Learning.