An i-vector GPLDA System for Speech based Emotion Recognition

被引：0
|
作者：
Gamage, Kalani Wataraka [1 ,2 ]
Sethu, Vidhyasaharan [1 ]
Phu Ngoc Le [1 ,2 ]
Ambikairajah, Eliathamby [1 ,2 ]
机构：
[1] UNSW, Sch Elect Engn & Telecommun, Kensington, NSW, Australia
[2] Natl ICT Australia NICTA, ATP Res Lab, Sydney, NSW, Australia
来源：
2015 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA) | 2015年
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, we propose the use of a Gaussian Probabilistic Linear Discriminant Analysis (GPLDA) back-end for utterance level emotion classification based on i-vectors representing the distribution of frame level MFCC features. Experimental results based on the IEMOCAP corpus show that the GPLDA back-end outperforms an SVM based back-end while being less sensitive to i-vector dimensionality, making the proposed framework more robust to parameter tuning during system development.
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页码：289 / 292
页数：4
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