Cross lingual speech emotion recognition using canonical correlation analysis on principal component subspace

Hesam Sagha; Jun Deng; Maryna Gavryukova; Jing Han; Bjorn Schuller

doi:10.1109/ICASSP.2016.7472789

Cross lingual speech emotion recognition using canonical correlation analysis on principal component subspace

Hesam Sagha, Jun Deng, Maryna Gavryukova, Jing Han, Bjorn Schuller

Chair of Health Informatics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

41 Scopus citations

Abstract

This paper proposes an analytical approach based on Kernel Canonical Correlation Analysis (KCCA) for domain adaptation. To generate paired instances for KCCA, we mapped source and target data onto both source and target principal components. We performed pair-wise domain adaptation between four emotional speech corpora with different languages (English, German, Italian, and Polish) to validate the approach. We compared our approach with the Shared-Hidden-Layer Auto-Encoder (SHLA) and kernel based principal components. On average, the proposed approach yields higher classification performance.

Original language	English
Title of host publication	2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5800-5804
Number of pages	5
ISBN (Electronic)	9781479999880
DOIs	https://doi.org/10.1109/ICASSP.2016.7472789
State	Published - 18 May 2016
Event	41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China Duration: 20 Mar 2016 → 25 Mar 2016

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2016-May
ISSN (Print)	1520-6149

Conference

Conference	41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
Country/Territory	China
City	Shanghai
Period	20/03/16 → 25/03/16

Keywords

Transfer learning
canonical correlation analysis
cross lingual
domain adaptation
emotion recognition

Access to Document

10.1109/ICASSP.2016.7472789

Cite this

Sagha, H., Deng, J., Gavryukova, M., Han, J., & Schuller, B. (2016). Cross lingual speech emotion recognition using canonical correlation analysis on principal component subspace. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings (pp. 5800-5804). Article 7472789 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2016-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2016.7472789

Sagha, Hesam ; Deng, Jun ; Gavryukova, Maryna et al. / Cross lingual speech emotion recognition using canonical correlation analysis on principal component subspace. 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 5800-5804 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

@inproceedings{ad75efe5a5fb4a18909c2ac585d960d6,

title = "Cross lingual speech emotion recognition using canonical correlation analysis on principal component subspace",

abstract = "This paper proposes an analytical approach based on Kernel Canonical Correlation Analysis (KCCA) for domain adaptation. To generate paired instances for KCCA, we mapped source and target data onto both source and target principal components. We performed pair-wise domain adaptation between four emotional speech corpora with different languages (English, German, Italian, and Polish) to validate the approach. We compared our approach with the Shared-Hidden-Layer Auto-Encoder (SHLA) and kernel based principal components. On average, the proposed approach yields higher classification performance.",

keywords = "Transfer learning, canonical correlation analysis, cross lingual, domain adaptation, emotion recognition",

author = "Hesam Sagha and Jun Deng and Maryna Gavryukova and Jing Han and Bjorn Schuller",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 ; Conference date: 20-03-2016 Through 25-03-2016",

year = "2016",

month = may,

day = "18",

doi = "10.1109/ICASSP.2016.7472789",

language = "English",

series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "5800--5804",

booktitle = "2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings",

}

Sagha, H, Deng, J, Gavryukova, M, Han, J & Schuller, B 2016, Cross lingual speech emotion recognition using canonical correlation analysis on principal component subspace. in 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings., 7472789, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 2016-May, Institute of Electrical and Electronics Engineers Inc., pp. 5800-5804, 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016, Shanghai, China, 20/03/16. https://doi.org/10.1109/ICASSP.2016.7472789

Cross lingual speech emotion recognition using canonical correlation analysis on principal component subspace. / Sagha, Hesam; Deng, Jun; Gavryukova, Maryna et al.
2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. p. 5800-5804 7472789 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2016-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Cross lingual speech emotion recognition using canonical correlation analysis on principal component subspace

AU - Sagha, Hesam

AU - Deng, Jun

AU - Gavryukova, Maryna

AU - Han, Jing

AU - Schuller, Bjorn

PY - 2016/5/18

Y1 - 2016/5/18

N2 - This paper proposes an analytical approach based on Kernel Canonical Correlation Analysis (KCCA) for domain adaptation. To generate paired instances for KCCA, we mapped source and target data onto both source and target principal components. We performed pair-wise domain adaptation between four emotional speech corpora with different languages (English, German, Italian, and Polish) to validate the approach. We compared our approach with the Shared-Hidden-Layer Auto-Encoder (SHLA) and kernel based principal components. On average, the proposed approach yields higher classification performance.

AB - This paper proposes an analytical approach based on Kernel Canonical Correlation Analysis (KCCA) for domain adaptation. To generate paired instances for KCCA, we mapped source and target data onto both source and target principal components. We performed pair-wise domain adaptation between four emotional speech corpora with different languages (English, German, Italian, and Polish) to validate the approach. We compared our approach with the Shared-Hidden-Layer Auto-Encoder (SHLA) and kernel based principal components. On average, the proposed approach yields higher classification performance.

KW - Transfer learning

KW - canonical correlation analysis

KW - cross lingual

KW - domain adaptation

KW - emotion recognition

UR - http://www.scopus.com/inward/record.url?scp=84973279544&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.2016.7472789

DO - 10.1109/ICASSP.2016.7472789

M3 - Conference contribution

AN - SCOPUS:84973279544

T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

SP - 5800

EP - 5804

BT - 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016

Y2 - 20 March 2016 through 25 March 2016

ER -

Sagha H, Deng J, Gavryukova M, Han J, Schuller B. Cross lingual speech emotion recognition using canonical correlation analysis on principal component subspace. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2016. p. 5800-5804. 7472789. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/ICASSP.2016.7472789

Cross lingual speech emotion recognition using canonical correlation analysis on principal component subspace

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this