Gender and emotion recognition with implicit user signals

Maneesh Bilalpur, Seyed Mostafa Kia, Manisha Chawla, Tat Seng Chua, Ramanathan Subramanian

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

9 Citations (Scopus)

Abstract

We examine the utility of implicit user behavioral signals captured using low-cost, off-the-shelf devices for anonymous gender and emotion recognition. A user study designed to examine male and female sensitivity to facial emotions confirms that females recognize (especially negative) emotions quicker and more accurately than men, mirroring prior findings. Implicit viewer responses in the form of EEG brain signals and eye movements are then examined for existence of (a) emotion and gender-specific patterns from event-related potentials (ERPs) and fixation distributions and (b) emotion and gender discriminability. Experiments reveal that (i) Gender and emotion-specific differences are observable from ERPs, (ii) multiple similarities exist between explicit responses gathered from users and their implicit behavioral signals, and (iii) Significantly above-chance (≈70%) gender recognition is achievable on comparing emotion-specific EEG responses- gender differences are encoded best for anger and disgust. Also, fairly modest valence (positive vs negative emotion) recognition is achieved with EEG and eye-based features.

Original languageEnglish
Title of host publicationICMI 2017 - Proceedings of the 19th ACM International Conference on Multimodal Interaction
EditorsEdward Lank, Eve Hoggan, Sriram Subramanian, Alessandro Vinciarelli, Stephen A. Brewster
Place of PublicationUnited States
PublisherAssociation for Computing Machinery (ACM)
Pages379-387
Number of pages9
ISBN (Electronic)9781450355438
DOIs
Publication statusPublished - 3 Nov 2017
Externally publishedYes
Event19th ACM International Conference on Multimodal Interaction, ICMI 2017 - Glasgow, United Kingdom
Duration: 13 Nov 201717 Nov 2017

Publication series

NameICMI 2017 - Proceedings of the 19th ACM International Conference on Multimodal Interaction
Volume2017-January

Conference

Conference19th ACM International Conference on Multimodal Interaction, ICMI 2017
CountryUnited Kingdom
CityGlasgow
Period13/11/1717/11/17

Fingerprint Dive into the research topics of 'Gender and emotion recognition with implicit user signals'. Together they form a unique fingerprint.

Cite this