Emotion Recognition in Marathi Language by using Fast Fourier Transform

Authors

  • Shinde Ashok R Punyashlok Ahilyadevi Holkar Solapur University, Solapur, India
  • Agnihotri Prashant P Swami Ramanand Teerth University, Sub-Centre Latur, India
  • Raut SD Punyashlok Ahilyadevi Holkar Solapur University, Solapur, India
  • Khanale Prakash B D.S.M. College, Parbhani, India

DOI:

https://doi.org/10.26438/ijcse/v7i10.4347

Keywords:

Emotion Recognition, SER, AER

Abstract

Emotion Recognition is a recent research area which can be applied in various applications. Speech Emotion is useful in E-learning, medical and in entertainment. The proposed work focuses on emotion recognition using Fast Fourier Transform and Marathi speech database. In this work six emotions are considered and Fast Fourier Transform is used for feature extraction and as a major feature for finding specific emotion. The Marathi words which represents the emotion like surprise and sad like Are Bapre (अरे बापरे ! ), Kiti Wilakshan (किती विलक्षण ! ), Are Deva (अरे देवा !) etc are used as a speech samples for analysis purpose. This paper highlights the overview of existing speech database as well as the newly developed Marathi emotional speech database. In this proposed work total 52 Marathi utterances are used in the experimental purpose. Fourier Transform is used to convert time domain signal into Frequency domain signal. The proposed experimental work gives 100% recognition rate for surprise and disgust emotion. Similarly 90% accuracy for sad emotion and 87.5% accuracy got for fear and angry emotion. The overall average recognition rate for six emotions is 93%. Very less accuracy rate i.e 62.5% got for happy emotion.

References

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Published

2019-10-31
CITATION
DOI: 10.26438/ijcse/v7i10.4347
Published: 2019-10-31

How to Cite

[1]
R. Shinde Ashok, P. Agnihotri Prashant, S. Raut, and B. Khanale Prakash, “Emotion Recognition in Marathi Language by using Fast Fourier Transform”, Int. J. Comp. Sci. Eng., vol. 7, no. 10, pp. 43–47, Oct. 2019.

Issue

Section

Research Article