Emotional speech classification in consensus building

Ning He, Shuoqing Yao, Osamu Yoshie

研究成果: Conference contribution

1 引用 (Scopus)

抜粋

In this paper we introduce a novel approach that robust automatic speech features recognition of one's emotion is achieved in a classification model named decision forest. The 13th order of Mel-frequency ceptstrum coefficients (MFCC) vector is processed as the multivariate data that will be imported to our classifier. In order to draw underlying and inductive information behind the MFCC feature, our decision forest classifier contains two stages to make classification, a supervised clustering based pattern extraction stage and a soft discretization based decision forest stage. Finally, a Japanese emotion corpus used for training and evaluation is described in detail. The results in recognition of six discrete emotions exceeded a mean value of 81% recognition rate.

元の言語English
ホスト出版物のタイトル2014 10th International Conference on Communications, COMM 2014 - Conference Proceedings
出版者Institute of Electrical and Electronics Engineers Inc.
ISBN(印刷物)9781479923854
DOI
出版物ステータスPublished - 2014 1 1
イベント2014 10th International Conference on Communications, COMM 2014 - Bucharest, Romania
継続期間: 2014 5 292014 5 31

出版物シリーズ

名前IEEE International Conference on Communications
ISSN(印刷物)1550-3607

Conference

Conference2014 10th International Conference on Communications, COMM 2014
Romania
Bucharest
期間14/5/2914/5/31

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

フィンガープリント Emotional speech classification in consensus building' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

  • これを引用

    He, N., Yao, S., & Yoshie, O. (2014). Emotional speech classification in consensus building. : 2014 10th International Conference on Communications, COMM 2014 - Conference Proceedings [6866670] (IEEE International Conference on Communications). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICComm.2014.6866670