Speech Emotion Recognition of Intelligent Virtual Companion for Solitudinarian

DOI

10.2991/978-94-6463-082-4_14How to use a DOI?

Keywords

Speech Emotion Recognition; MLP classifier; MFCC; Emotion Recognition; Long Term Short Memory (LTSM)

Abstract

Human emotions are essential to recognize the behaviour and the state of mind of a person. Emotion detection through speech signals has started to receive more attention lately. Living alone could be hard for some people due to the lack of social interaction, as they might develop a series of negative emotions daily. Furthermore, there are some unavoidable circumstances when family members need to live away from their families, leaving their old parents to live alone. These circumstances may cause parents to experience anxiety or a decline in mental health, which is a major cause for concern for their children. This is where assisted living technology can come in to support. This research proposes the design and development of a speech emotion recognition system for solitary people to detect and monitor their state of mind as well as their daily emotional behaviour. The research has three main contributions. First, to implement a real-time system based on audio where we can predict emotions from recorded human voices via deep learning. Secondly, a model has been designed to use data normalization and data augmentation techniques for advanced classification. Finally, a speech emotion detection system has been created using a Long Short Term Memory (LSTM) recurrent neural network. This research aims to study solitary person activities at any time at home. The resulting system will be used for mental health monitoring.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Mutaz Alnahhas
AU  - Tan Wooi Haw
AU  - Ooi Chee Pun
PY  - 2022
DA  - 2022/12/23
TI  - Speech Emotion Recognition of Intelligent Virtual Companion for Solitudinarian
BT  - Proceedings of the Multimedia University Engineering Conference (MECON 2022)
PB  - Atlantis Press
SP  - 132
EP  - 138
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-082-4_14
DO  - 10.2991/978-94-6463-082-4_14
ID  - Alnahhas2022
ER  -