Class-level spectral features for emotion recognition

@article{Bitouk2010ClasslevelSF,
  title={Class-level spectral features for emotion recognition},
  author={Dmitri Bitouk and Ragini Verma and Ani Nenkova},
  journal={Speech communication},
  year={2010},
  volume={52 7-8},
  pages={613-625}
}
The most common approaches to automatic emotion recognition rely on utterance level prosodic features. Recent studies have shown that utterance level statistics of segmental spectral features also contain rich information about expressivity and emotion. In our work we introduce a more fine-grained yet robust set of spectral features: statistics of Mel-Frequency Cepstral Coefficients computed over three phoneme type classes of interest-stressed vowels, unstressed vowels and consonants in the… CONTINUE READING
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