Choice of a classifier, based on properties of a dataset: case study-speech emotion recognition-Reference-Cited by-同舟云学术

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Choice of a classifier, based on properties of a dataset: case study-speech emotion recognition

Published:2018-02-01 Issue:1 Volume:21 Page:167-183
ISSN:1381-2416
Container-title:International Journal of Speech Technology
language:en
Short-container-title:Int J Speech Technol

Author:

Koolagudi Shashidhar G.,Murthy Y. V. Srinivasa^ORCID,Bhaskar Siva P.

Publisher

Springer Science and Business Media LLC

Subject

Computer Vision and Pattern Recognition,Linguistics and Language,Human-Computer Interaction,Language and Linguistics,Software

Link

http://link.springer.com/article/10.1007/s10772-018-9495-8/fulltext.html

Reference132 articles.

1. Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716–723.

2. Anagnostopoulos, C.-N., Iliou, T., & Giannoukos, I. (2012). Features and classifiers for emotion recognition from speech: A survey from 2000 to 2011. Artificial Intelligence Review, 43, 1–23.

3. Ananthapadmanabha, T., & Yegnanarayana, B. (1979). Epoch extraction from linear prediction residual for identification of closed glottis interval. IEEE Transactions on Acoustics, Speech and Signal Processing, 27(4), 309–319.

4. Banse, R., & Scherer, K. R. (1996). Acoustic profiles in vocal emotion expression. Journal of Personality and Social Psychology, 70(3), 614.

5. Bhatti, M. W., Wang, Y., & Guan, L. (2004). A neural network approach for human emotion recognition in speech. In ISCAS’04. Proceedings of the 2004 international symposium on Circuits and systems, 2004, (Vol. 2, pp II–181). IEEE

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