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Speech Emotion Recognition Using Spectral Entropy

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Intelligent Robotics and Applications (ICIRA 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5315))

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Abstract

This paper proposes a Gaussian Mixture Model (GMM)–based speech emotion recognition methods using four feature parameters; 1) Fast Fourier Transform(FFT) spectral entropy, 2) delta FFT spectral entropy, 3) Mel-frequency Filter Bank (MFB) spectral entropy, 4) delta MFB spectral entropy. In addition, we use four emotions in a speech database including anger, sadness, happiness, and neutrality. We perform speech emotion recognition experiments using each pre-defined emotion and gender. The experimental results show that the proposed emotion recognition using FFT spectral-based entropy and MFB spectral-based entropy performs better than existing emotion recognition based on GMM using energy, Zero Crossing Rate (ZCR), Linear Prediction Coefficient (LPC), and pitch parameters.

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Author information

Authors and Affiliations

  1. School of Information and Communication Engineering, Sungkyunkwan University, 300, Chunchun-dong, Jangan-gu, Suwon, Kyungki-do, 440-746, Korea

    Woo-Seok Lee, Yong-Wan Roh, Dong-Ju Kim, Jung-Hyun Kim & Kwang-Seok Hong

Authors
  1. Woo-Seok Lee
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  2. Yong-Wan Roh
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  3. Dong-Ju Kim
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  4. Jung-Hyun Kim
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  5. Kwang-Seok Hong
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Editor information

Editors and Affiliations

  1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China

    Caihua Xiong

  2. The Institute of Industrial Research, University of Portsmouth, UK

    Honghai Liu

  3. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 430074, Wuhan, P. R. China

    Yongan Huang  & Youlun Xiong  & 

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© 2008 Springer-Verlag Berlin Heidelberg

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Lee, WS., Roh, YW., Kim, DJ., Kim, JH., Hong, KS. (2008). Speech Emotion Recognition Using Spectral Entropy. In: Xiong, C., Liu, H., Huang, Y., Xiong, Y. (eds) Intelligent Robotics and Applications. ICIRA 2008. Lecture Notes in Computer Science(), vol 5315. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88518-4_6

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  • DOI: https://doi.org/10.1007/978-3-540-88518-4_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88516-0

  • Online ISBN: 978-3-540-88518-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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