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Information Journal Paper

Title

EMOTION RECOGNITION AND EMOTION SPOTTING IMPROVEMENT USING FORMANT-RELATED FEATURES

Pages

  1-8

Abstract

 Emotion has an important role in naturalness of man-machine communication and many researchers investigate computerized EMOTION RECOGNITION from speech in the recent decades. In this paper, the effect of formant-related features on improving the performance of emotion detection systems is experimented. To do this, various forms and combinations of the first three FORMANTS are concatenated to a popular feature vector and GAUSSIAN MIXTURE MODELs are used as classifiers. Experimental results show average recognition rate of 69% in four emotional states and noticeable performance improvement by adding only one formant-related parameter to feature vector. The architecture of hybrid EMOTION RECOGNITION/spotting is also proposed based on the developed models.

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    Cite

    APA: Copy

    GHARAVIAN, D., & SHEIKHAN, M.. (2010). EMOTION RECOGNITION AND EMOTION SPOTTING IMPROVEMENT USING FORMANT-RELATED FEATURES. MAJLESI JOURNAL OF ELECTRICAL ENGINEERING, 4(4 (15)), 1-8. SID. https://sid.ir/paper/564326/en

    Vancouver: Copy

    GHARAVIAN D., SHEIKHAN M.. EMOTION RECOGNITION AND EMOTION SPOTTING IMPROVEMENT USING FORMANT-RELATED FEATURES. MAJLESI JOURNAL OF ELECTRICAL ENGINEERING[Internet]. 2010;4(4 (15)):1-8. Available from: https://sid.ir/paper/564326/en

    IEEE: Copy

    D. GHARAVIAN, and M. SHEIKHAN, “EMOTION RECOGNITION AND EMOTION SPOTTING IMPROVEMENT USING FORMANT-RELATED FEATURES,” MAJLESI JOURNAL OF ELECTRICAL ENGINEERING, vol. 4, no. 4 (15), pp. 1–8, 2010, [Online]. Available: https://sid.ir/paper/564326/en

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