A feature selection and feature fusion combination method for speaker-independent speech emotion recognition

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

Volumn , Issue , 2014, Pages 4808-4812

  Jin, Yun ^a,b   Song, Peng ^a   Zheng, Wenming ^c   Zhao, Li ^a  

^a SOUTHEAST UNIVERSITY   (China)

^b JIANGSU NORMAL UNIVERSITY   (China)

^c Southeast University   (China)

Author keywords

feature fusion; feature selection; multiple kernel learning; speech emotion recognition

Indexed keywords

ELECTRICAL ENGINEERING; FEATURE EXTRACTION;

COMBINATION METHOD; CROSS VALIDATION; FEATURE FUSION; FEATURE SETS; MULTIPLE KERNEL LEARNING; SPARSE FEATURES; SPEAKER INDEPENDENTS; SPEECH EMOTION RECOGNITION;

SIGNAL PROCESSING;

EID: 84905226801     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2014.6854515     Document Type: Conference Paper

References (19)

1. Bjorn Schuller, Anton Batliner, Stefan Steidl, and Dino Seppi, "Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge, " Speech Communication, vol. 53, no. 9, pp. 1062-1087, 2011.
2. Ian Jolliffe, Principal component analysis, Wiley Online Library, 2005.
3. Keinosuke Fukunaga, Introduction to statistical pattern recognition, Academic Pr, 1990.
4. Lei Yu and Huan Liu, "Feature selection for highdimensional data: A fast correlation-based filter solution, " in MACHINE LEARNING-INTERNATIONAL WORKSHOP THEN CONFERENCE-, 2003, vol. 20, p. 856.
5. Bjorn Schuller, Stephan Reiter, R Muller, Marc Al-Hames, Manfred Lang, and Gerhard Rigoll, "Speaker independent speech emotion recognition by ensemble classification, " in Multimedia and Expo, 2005. ICME 2005. IEEE International Conference on. IEEE, 2005, pp. 864-867.
6. Dimitrios Ververidis and Constantine Kotropoulos, "Fast and accurate sequential floating forward feature selection with the bayes classifier applied to speech emotion recognition, " Signal Processing, vol. 88, no. 12, pp. 2956-2970, 2008.
7. Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, and Vladimir Vapnik, "Feature selection for svms, " Advances in neural information processing systems, pp. 668-674, 2001.
8. Niranjan Subrahmanya and Yung C Shin, "Sparse multiple kernel learning for signal processing applications, " Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 32, no. 5, pp. 788-798, 2010.
9. Francis R Bach, Gert RG Lanckriet, and Michael I Jordan, "Multiple kernel learning, conic duality, and the smo algorithm, " in Proceedings of the twenty-first international conference on Machine learning. ACM, 2004, p. 6.
10. Alain Rakotomamonjy, Francis Bach, Stephane Canu, Yves Grandvalet, et al., "Simplemkl, " Journal of Machine Learning Research, vol. 9, pp. 2491-2521, 2008.
11. Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King, and Michael R Lyu, "Simple and efficient multiple kernel learning by group lasso, " in Proceedings of the 27th International Conference on Machine Learning, 2010, pp. 1175-1182.
12. JIN Yun, SONG Peng, ZHENG Wenming, ZHAO Li, and XIN Minghai, "Speaker-independent speech emotion recognition based on two-layer multiple kernel learning, " IEICE TRANSACTIONS on Information and Systems, vol. 96, no. 10, pp. 2286-2289, 2013.
13. Felix Burkhardt, Astrid Paeschke, Miriam Rolfes, Walter Sendlmeier, and Benjamin Weiss, "A database of german emotional speech, " in Proc. Interspeech, 2005.
14. Florian Eyben, Martin Wollmer, and Bjorn Schuller, "Openearłintroducing the munich open-source emotion and affect recognition toolkit, " in Affective Computing and Intelligent Interaction and Workshops, 2009. ACII 2009. 3rd International Conference on. IEEE, 2009, pp. 1-6.
15. A. Tawari and M.M. Trivedi, "Speech emotion analysis: exploring the role of context, " Multimedia, IEEE Transactions on, vol. 12, no. 6, pp. 502-509, 2010.
16. D. Bitouk, R. Verma, and A. Nenkova, "Class-level spectral features for emotion recognition, " Speech Communication, vol. 52, no. 7, pp. 613-625, 2010.
17. P. Ruvolo, I. Fasel, and J.R. Movellan, "A learning approach to hierarchical feature selection and aggregation for audio classification, " Pattern Recognition Letters, vol. 31, no. 12, pp. 1535-1542, 2010.
18. Shiqing Zhang, Xiaoming Zhao, and Bicheng Lei, "Speech emotion recognition using an enhanced kernel isomap for human-robot interaction, " INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, vol. 10, 2013.
19. Mayank Bhargava and Tim Polzehl, "Improving automatic emotion recognition from speech using rhythm and temporal feature, " arXiv preprint arXiv:1303.1761, 2013