The effect of silence feature in dimensional speech emotion recognition

Bagus Tris Atmaja, Masato Akagi

Research output: Contribution to journalConference articlepeer-review

7 Citations (Scopus)


Silence is a part of human-to-human communication, which can be a clue for human emotion perception. For automatic emotion recognition by a computer, it is not clear whether silence is useful to determine human emotion within a speech. This paper presents an investigation of the effect of using silence feature in dimensional emotion recognition. Since the silence feature is extracted per utterance, we grouped the silence feature with high statistical functions from a set of acoustic features. The result reveals that the silence features affect the arousal dimension more than other emotion dimensions. The proper choice of a threshold factor in the calculation of silence feature improved the performance of dimensional speech emotion recognition performance, in terms of a concordance correlation coefficient. On the other side, improper choice of that factor leads to a decrease in performance by using the same architecture.

Original languageEnglish
Pages (from-to)26-30
Number of pages5
JournalProceedings of the International Conference on Speech Prosody
Publication statusPublished - 2020
Event10th International Conference on Speech Prosody 2020 - Tokyo, Japan
Duration: 25 May 202028 May 2020


  • Affective computing
  • Dimensional emotion
  • Silence feature
  • Silence threshold
  • Speech emotion recognition


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