Citation
Ong, Kah Liang and Lee, Chin Poo and Lim, Heng Siong (2022) Speech Emotion Classification with Deep Learning. In: Postgraduate Colloquium December 2022, 1-15 December 2022, Multimedia University, Malaysia. (Unpublished)
Text
43_ONG KAH LIANG_FIST.pdf - Submitted Version Restricted to Registered users only Download (621kB) |
Abstract
Deep neural networks have been applied to speech emotion recognition. • Employed for automatic feature extraction from the audio signal in the related field. • Audio signals are essential to have the pre-processing step. • Quality of voice has a direct influence on the speech emotion recognition results. • Acoustic speech features. • Word, phoneme, phrase. • Spectral features. • Mel-frequency Cepstral Coefficients (MFCC).
Item Type: | Conference or Workshop Item (Poster) |
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Uncontrolled Keywords: | Deep learning, Machine learning |
Subjects: | Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science |
Divisions: | Faculty of Information Science and Technology (FIST) |
Depositing User: | Ms Nurul Iqtiani Ahmad |
Date Deposited: | 19 Dec 2022 04:01 |
Last Modified: | 19 Dec 2022 04:01 |
URII: | http://shdl.mmu.edu.my/id/eprint/10907 |
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