Speech Emotion Recognition using Machine Learning

Authors

  • Ashwin V. Gatty Student, Department of Computer Science and Engineering, Srinivas Institute of Technology, Mangalore, India
  • G. S. Shivakumar Professor, Department of Computer Science and Engineering, Srinivas Institute of Technology, Mangalore, India
  • Kiran Shetty Student, Department of Computer Science and Engineering, Srinivas Institute of Technology, Mangalore, India

Keywords:

Language, Communication, Speech recognition, Interaction

Abstract

Language is a basic need for the humans to communicate and speech for its primary medium. Spoken interaction in both between human interlocutors and between humans and machines is inescapably embedded within the laws and conditions of Communication, which comprise the encoding and decoding of meaning as well because the mere transmission of messages over an acoustical channel. Here we deal with this interaction between the human and machine through synthesis and recognition applications. Speech recognition, involves capturing and digitizing the sound waves, converting them to basic language units or phonemes, constructing words from phonemes and contextually analyzing the words to make sure correct spelling for words that sound alike. Speech Recognition is the ability of a computer to recognize the caller’s answers to move along the flow of the cell. Emphasis is given on the modeling of speech units and grammar on the basic of hidden markov model and neural networks. Speech recognition allows you to provide input to an application with your voice. The applications and limitations on above subject enlighten the impact of speech processing in our modern technical field.

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Published

2021-07-15

How to Cite

[1]
A. V. Gatty, G. S. Shivakumar, and K. Shetty, “Speech Emotion Recognition using Machine Learning”, IJRESM, vol. 4, no. 7, pp. 136–138, Jul. 2021.

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Articles