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Emotion Recognition Based on Frequency Analysis of Speech Signal

  • Sim, Kwee-Bo (School of Electronic Engineering, Chung-Ang University) ;
  • Park, Chang-Hyun (School of Electronic Engineering, Chung-Ang University) ;
  • Lee, Dong-Wook (School of Electronic Engineering, Chung-Ang University) ;
  • Joo, Young-Hoon (School of Electronic and Information Engineering, Kunsan National University)
  • Published : 2002.06.01

Abstract

In this study, we find features of 3 emotions (Happiness, Angry, Surprise) as the fundamental research of emotion recognition. Speech signal with emotion has several elements. That is, voice quality, pitch, formant, speech speed, etc. Until now, most researchers have used the change of pitch or Short-time average power envelope or Mel based speech power coefficients. Of course, pitch is very efficient and informative feature. Thus we used it in this study. As pitch is very sensitive to a delicate emotion, it changes easily whenever a man is at different emotional state. Therefore, we can find the pitch is changed steeply or changed with gentle slope or not changed. And, this paper extracts formant features from speech signal with emotion. Each vowels show that each formant has similar position without big difference. Based on this fact, in the pleasure case, we extract features of laughter. And, with that, we separate laughing for easy work. Also, we find those far the angry and surprise.

Keywords

References

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Cited by

  1. The Feature Extraction Based on Texture Image Information for Emotion Sensing in Speech vol.14, pp.9, 2014, https://doi.org/10.3390/s140916692
  2. Time-Frequency Feature Representation Using Multi-Resolution Texture Analysis and Acoustic Activity Detector for Real-Life Speech Emotion Recognition vol.15, pp.1, 2015, https://doi.org/10.3390/s150101458