Earticle

초록

영어

In order to improve the recognition performance of the tradition KNN, we combined the contributions of each feature parameter for different emotions with the tradition KNN and proposed a Fuzzy KNN algorithm for speech emotion recognition. Four kinds of emotions’ recognition experiment has shown that the Fuzzy KNN we proposed not only keeps the tradition KNN’s advantages of fast recognition and easy realization, but also improves the recognition performance.

목차

Abstract
 1. Introduction
 2. Speech Emotion DaTablease
 3. Emotional Feature Analysis
  3.1. Time Construction Analysis
  3.2. Amplitude Construction Analysis
  3.3. Fundamental Frequency Construction Analysis
  3.4. Fundamental Frequency Construction Analysis
  3.5. Conclusion of Feature Analysis
 4. Speech Emotion Recognition Based on Fuzzy KNN
 5. Experiments
 6. Conclusion
 Acknowledgements
 References

키워드

저자

• Zhu Ming [ Yancheng Institute of Technology, College of Information Engineering, Yancheng 224051, China ]
• Zhou Feng [ Yancheng Institute of Technology, College of Information Engineering, Yancheng 224051, China ]
• Ji Zhengbiao [ Yancheng Institute of Technology, College of Information Engineering, Yancheng 224051, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605