AI-based Emotion Recognition System with Tensor Decomposition Optimized Pre-processing

Chia Yu Liao, Chia Yu Li, Wai Chi Fang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In this paper, we proposed to optimize a CNN-based emotion recognition system using EEG signal input by integrating a tensor decomposition pre-processing engine. Although CNNs have been proven to be a strong method to solve the classification of emotion accurately, the amount of required computation and memory remains a challenge for edge AI implementation. The tensor decomposition pre-processing engine proposed in this work efficiently identified the key hidden core tensors containing the most contributing features to the classification of emotion while removing the unnecessary redundant data affecting the amount of required computation and memory usage. This pre-processing engine effectively speeds up the AI acceleration by a factor of 3 and reduced the memory usage by 35% while keeping comparable classification performances with an average accuracy slightly higher by 4%.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665433280
DOIs
StatePublished - 2021
Event8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021 - Penghu, Taiwan
Duration: 15 Sep 202117 Sep 2021

Publication series

Name2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021

Conference

Conference8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
Country/TerritoryTaiwan
CityPenghu
Period15/09/2117/09/21

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