Emotion clustering based on probabilistic linear discriminant analysis

@inproceedings{Mehrabani2015EmotionCB,
  title={Emotion clustering based on probabilistic linear discriminant analysis},
  author={Mahnoosh Mehrabani and Ozlem Kalinli and Ruxin Chen},
  booktitle={INTERSPEECH},
  year={2015}
}
This study proposes an emotion clustering method based on Probabilistic Linear Discriminant Analysis (PLDA). Each emotional utterance is modeled as a GMM mean supervector. Hierarchical clustering is applied to cluster supervectors that represent similar emotions using a likelihood ratio from a PLDA model. The PLDA model can be trained with a different emotional database from the test data, with different emotion categories, speakers, or even languages. The advantage of using a PLDA model is… CONTINUE READING