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All Journal Bulletin of Electrical Engineering and Informatics
Jonathan Christian Setyono
Bina Nusantara University
Electrical & Electronics Engineering

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Data augmentation and enhancement for multimodal speech emotion recognition Jonathan Christian Setyono; Amalia Zahra
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5031

Abstract

Humans’ fundamental need is interaction with each other such as using conversation or speech. Therefore, it is crucial to analyze speech using computer technology to determine emotions. The speech emotion recognition (SER) method detects emotions in speech by examining various aspects. SER is a supervised method to decide the emotion class in speech. This research proposed a multimodal SER model using one of the deep learning based enhancement techniques, which is the attention mechanism. Additionally, this research addresses the imbalanced dataset problem in the SER field using generative adversarial networks (GAN) as a data augmentation technique. The proposed model achieved an excellent evaluation performance of 0.96 or 96% for the proposed GAN configuration. This work showed that the GAN method in the multimodal SER model could enhance performance and create a balanced dataset.
Co-Authors Amalia Zahra