Transfer learning for improving speech emotion classification accuracy

Latif, Siddique and Rana, Rajib and Younis, Shahzad and Qadir, Junaid and Epps, Julien (2018) Transfer learning for improving speech emotion classification accuracy. In: 19th Annual Conference of the International Speech Communication Association: Speech Research for Emerging Markets in Multilingual Societies (INTERSPEECH 2018), 2-6 Sept 2018, Hyderabad, India.


The majority of existing speech emotion recognition research focuses on automatic emotion detection using training and testing data from the same corpus collected under the same conditions. The performance of such systems has been shown to drop significantly in cross-corpus and cross-language scenarios. To address the problem, this paper exploits a transfer learning technique to improve the performance of speech emotion recognition systems that are novel in cross-language and cross-corpus scenarios. Evaluations on five different corpora in three different languages show that Deep Belief Networks (DBNs) offer better accuracy than previous approaches on cross-corpus emotion recognition, relative to a Sparse Autoencoder and Support Vector Machine (SVM) baseline system. Results also suggest that using a large number of languages for training and using a small fraction of the target data in training can significantly boost accuracy compared with baseline also for the corpus with limited training examples.

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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Copyright 2018 International Speech Communication Association (ISCA).
Faculty/School / Institute/Centre: Current - Institute for Resilient Regions
Faculty/School / Institute/Centre: Current - Institute for Resilient Regions
Date Deposited: 18 Feb 2019 01:11
Last Modified: 08 Jun 2021 00:24
Uncontrolled Keywords: transfer learning, cross-corpus, deep belief networks, sparse autoencoder, support vector machine
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
08 Information and Computing Sciences > 0806 Information Systems > 080699 Information Systems not elsewhere classified
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460212 Speech recognition
Socio-Economic Objectives (2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: doi:10.21437/Interspeech.2018-1625

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