Comparative Analysis of Dimension Reduction Techniques Over Classification Algorithms for Speech Emotion Recognition-Reference-Cited by-同舟云学术

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Comparative Analysis of Dimension Reduction Techniques Over Classification Algorithms for Speech Emotion Recognition

Published:2020 Issue: Volume: Page:170-184
ISSN:1867-8211
Container-title:Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
language:
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Author:

Biswas Aditi,Chakraborty Sovon,Rifat Abu Nuraiya Mahfuza Yesmin,Chowdhury Nadia Farhin,Uddin Jia

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-60036-5_12

Reference20 articles.

1. Angra, S., Ahuja, S.: Machine learning and its applications: a review. In: International Conference on Big Data Analytics and Computational Intelligence (ICBDAC), Chirala, India, p. 1 (2017). https://doi.org/10.1109/icbdaci.2017.8070809

2. Akçay, M.B., Oğuz, K.: Speech emotion recognition: emotional models, databases, features, preprocessing methods, supporting modalities and classifiers. Speech Commun. 116, 56–76 (2020). https://doi.org/10.1016/j.specom.2019.12.001

3. Kerkeni, L., Serrestou, Y.: Speech emotion recognition: methods and cases study. In: 10th International Conference on Agents and Artificial Intelligence, Funchal, Madeira, Portugal (January 2018). https://doi.org/10.5220/0006611601750182

4. Lugovic, S., Dunder, I., Horvat, M.: Techniques and applications of emotion recognition in speech. In: 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), Opatija, Croatia, pp. 1278–1283 (2016). https://doi.org/10.1109/mipro.2016.7522336

5. Sato, N., Obuchi, Y.: Emotion recognition using mel-frequency cepstral coefficients. Inf. Media Technol. 2(3), 835–848 (2007). https://doi.org/10.11185/imt.2.835

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