ISCA Archive Interspeech 2009
ISCA Archive Interspeech 2009

Emotion recognition using a hierarchical binary decision tree approach

Chi-Chun Lee, Emily Mower, Carlos Busso, Sungbok Lee, Shrikanth S. Narayanan

Emotion state tracking is an important aspect of human-computer and human-robot interaction. It is important to design task specific emotion recognition systems for real-world applications. In this work, we propose a hierarchical structure loosely motivated by Appraisal Theory for emotion recognition. The levels in the hierarchical structure are carefully designed to place the easier classification task at the top level and delay the decision between highly ambiguous classes to the end. The proposed structure maps an input utterance into one of the five-emotion classes through subsequent layers of binary classifications. We obtain a balanced recall on each of the individual emotion classes using this hierarchical structure. The performance measure of the average unweighted recall percentage on the evaluation data set improves by 3.3% absolute (8.8% relative) over the baseline model.

doi: 10.21437/Interspeech.2009-105

Cite as: Lee, C.-C., Mower, E., Busso, C., Lee, S., Narayanan, S.S. (2009) Emotion recognition using a hierarchical binary decision tree approach. Proc. Interspeech 2009, 320-323, doi: 10.21437/Interspeech.2009-105

  author={Chi-Chun Lee and Emily Mower and Carlos Busso and Sungbok Lee and Shrikanth S. Narayanan},
  title={{Emotion recognition using a hierarchical binary decision tree approach}},
  booktitle={Proc. Interspeech 2009},