Spontaneous Speech Emotion Recognition via Multiple Kernel Learning

@article{Zha2016SpontaneousSE,
  title={Spontaneous Speech Emotion Recognition via Multiple Kernel Learning},
  author={Cheng Zha and Jianwei Zheng and Xinran Zhang and Lu Zhao},
  journal={2016 Eighth International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)},
  year={2016},
  pages={621-623}
}
Speech emotion recognition has become an active topic in pattern recognition. Specifically, support vector machine (SVM) is an effective classifier due to the application of the nonlinear mapping function, which can map the data into high or ever infinite dimensional feature space. However, a single kernel function might not sufficient to describe the different properties of spontaneous speech emotion data and thus it can not produce a satisfactory decision function. To address this issue, we… CONTINUE READING
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Georgiou . " Behavioral signal processing : Deriving human behavioral informatics from speech and language

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