Cross-Language Speech Emotion Recognition Via Multiple Kernel Learning

被引:0
作者
Zha, Cheng [1 ]
机构
[1] Guizhou Univ, Guiyang 550025, Peoples R China
来源
2019 INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA) | 2019年
关键词
cross-language; Multiple kernel learning; Speech emotion recognition; nonlinear mapping function;
D O I
10.1109/ICSGEA.2019.00055
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
Due to the difference of the speaker's language, speech emotion recognition tasks often face the situation that training data are not fully representative of test data. Therefore, the space extended by a kernel function. might not sufficient to describe different properties of data and thus produce a satisfactory decision function. In this wok, we apply multiple kernel learning to recognize the speech emotion of cross-language. Compared to SVM, multiple kernel learning can achieve better performance in cross-language speech emotion recognition tasks.
引用
收藏
页码:208 / 209
页数:2
相关论文
共 5 条
  • [1] Bach Francis R, 2004, ICML, DOI 10.1145/1015330.1015424
  • [2] Feature Analysis and Evaluation for Automatic Emotion Identification in Speech
    Luengo, Iker
    Navas, Eva
    Hernaez, Inmaculada
    [J]. IEEE TRANSACTIONS ON MULTIMEDIA, 2010, 12 (06) : 490 - 501
  • [3] Emotion recognition from speech using global and local prosodic features
    Rao K.S.
    Koolagudi S.G.
    Vempada R.R.
    [J]. International Journal of Speech Technology, 2013, 16 (2) : 143 - 160
  • [4] Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge
    Schuller, Bjorn
    Batliner, Anton
    Steidl, Stefan
    Seppi, Dino
    [J]. SPEECH COMMUNICATION, 2011, 53 (9-10) : 1062 - 1087
  • [5] Automatic speech emotion recognition using modulation spectral features
    Wu, Siqing
    Falk, Tiago H.
    Chan, Wai-Yip
    [J]. SPEECH COMMUNICATION, 2011, 53 (05) : 768 - 785