A Comparative Study On Speech Emotion Recognition

Authors

  • Anushka Sandesara UG Student, U & P U. Patel Department of Computer Engineering, Chandubhai S. Patel Institute of Science and Technology, CHARUSAT, Changa, India
  • Shilpi Parikh UG Student, U & P U. Patel Department of Computer Engineering, Chandubhai S. Patel Institute of Science and Technology, CHARUSAT, Changa, India
  • Pratyay Sapovadiya UG Student, U & P U. Patel Department of Computer Engineering, Chandubhai S. Patel Institute of Science and Technology, CHARUSAT, Changa, India
  • Mrugendrasinh Rahevar Assistant Professor, U & P U. Patel Department of Computer Engineering, Chandubhai S. Patel Institute of Science and Technology, CHARUSAT, Changa, India

DOI:

https://doi.org/10.47607/ijresm.2020.366

Keywords:

Deep learning, Machine learning, Speech recognition

Abstract

Today's world has been "Chatting" with the machines for a long time. With the first known research paper by Daellert et. al on this topic, we can say that discussions on Speech Emotion Recognition technology have been there for such a long time and have been evolving and increasing its applications in our life. Although worthy of these many applications, speech emotion recognition is a challenging task as emotion is a subjective thing. Not all humans are the same, each human deals differently with emotions. There are no common criteria or steps to categorize emotions. Forget computers, even we humans at times fail to read the emotions behind the other person. This paper provides the list of some speech emotion recognition methods and a glimpse of method used.

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Published

08-11-2020

Issue

Vol. 3 No. 11 (2020)

Section

Articles

License

Copyright (c) 2020 Anushka Sandesara, Shilpi Parikh, Pratyay Sapovadiya, Mrugendrasinh Rahevar

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
A. Sandesara, S. Parikh, P. Sapovadiya, and M. Rahevar, “A Comparative Study On Speech Emotion Recognition”, IJRESM, vol. 3, no. 11, pp. 25–35, Nov. 2020, doi: 10.47607/ijresm.2020.366.