A DFC taxonomy of Speech emotion recognition based on convolutional neural network from speech signal

Surendra Malla, Abeer Alsadoon, Simi Kamini Bajaj

Research output: Book chapter/Published conference paperConference paperpeer-review

3 Citations (Scopus)

Abstract

Speech is an efficient agent to explicit attitude and emotions via language. The crucial task for the researchers is to find out the emotions through the speech utterance and eliminating the noise from a raw speech data. The goal of this research paper is to explore the latest journal papers in the field of convolutional neural network-based speech emotion recognition (SER) models related with the specific problem and provide a best solution which can recognize emotion in the speech from the speech signal.The components of this proposed system are data, feature extraction and classification (DFC) that helps to assist in the implementation and evaluating the system. We propose the DFC taxonomy which will assist the end users in recognition of the emotion from the speech signal and making the artificial intelligence (AI) more robust by using convolutional neural network, facilitating a huge presence in the future system.The system evaluates a state-of-the-art model that is associated to the convolutional neural network-based speech emotion recognition which presents and validates the DFC components. Based on system completeness, system acceptance, and by classifying 30 state-of-the-art journal research papers in the domain, components are evaluated, verified and validated.The benefaction of this research paper is the critical analysis in the latest literature that are available on the convolutional neural network-based system which can recognize the emotion by extracting the features from the speech signal so that accurate recognition of emotion can be made. Also, highlighting the importance of DFC taxonomy.

Original languageEnglish
Title of host publication2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages10
ISBN (Electronic)9781728194370
ISBN (Print)9781728194387 (Print on demand)
DOIs
Publication statusE-pub ahead of print - 09 Mar 2021
Event5th IEEE International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2020: CITISIA 2020 - Charles Sturt University Sydney campus, Sydney, Australia
Duration: 25 Nov 202027 Nov 2020
https://web.archive.org/web/20201128085551/https://ieee-citisia.org/ (Conference website)
https://web.archive.org/web/20210124015105/https://ieee-citisia.org/wp-content/uploads/2020/11/Conference-Program-new1.pdf (Conference program)
https://ieeexplore.ieee.org/xpl/conhome/9371766/proceeding?pageNumber=4 (Full paper proceedings)

Publication series

NameCITISIA 2020 - IEEE Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, Proceedings

Conference

Conference5th IEEE International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2020
Country/TerritoryAustralia
CitySydney
Period25/11/2027/11/20
OtherThe “Conference on Innovative Technologies in Intelligent Systems & Industrial Applications” (CITISIA) is a student conference that aims to provide students of higher learning institutions with a platform for presenting their own projects. It is also a measure of recognition of students’ professional and technical achievements – by industries and international organizations such as IEEE. This conference is designed to facilitate exchanges of ideas through communication, networking and learning from others, for students and IEEE Chapters in terms of greater collaboration.
Internet address

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