BigEAR: Inferring the Ambient and Emotional Correlates from Smartphone-Based Acoustic Big Data

Harishchandra Dubey, Matthias R. Mehl, Kunal Mankodiya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

Abstract

This paper presents a novel BigEAR big data framework that employs psychological audio processing chain (PAPC) to process smartphone-based acoustic big data collected when the user performs social conversations in naturalistic scenarios. The overarching goal of BigEAR is to identify moods of the wearer from various activities such as laughing, singing, crying, arguing, and sighing. These annotations are based on ground truth relevant for psychologists who intend to monitor/infer the social context of individuals coping with breast cancer. We pursued a case study on couples coping with breast cancer to know how the conversations affect emotional and social well being. In the state-of-the-art methods, psychologists and their team have to hear the audio recordings for making these inferences by subjective evaluations that not only are time-consuming and costly, but also demand manual data coding for thousands of audio files. The BigEAR framework automates the audio analysis. We computed the accuracy of BigEAR with respect to the ground truth obtained from a human rater. Our approach yielded overall average accuracy of 88.76% on real-world data from couples coping with breast cancer.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE 1st International Conference on Connected Health
Subtitle of host publicationApplications, Systems and Engineering Technologies, CHASE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages78-83
Number of pages6
ISBN (Electronic)9781509009435
DOIs
StatePublished - Aug 16 2016
Event1st IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2016 - Washington, United States
Duration: Jun 27 2016Jun 29 2016

Publication series

NameProceedings - 2016 IEEE 1st International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2016

Other

Other1st IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2016
CountryUnited States
CityWashington
Period6/27/166/29/16

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems and Management
  • Biomedical Engineering
  • Computer Networks and Communications
  • Hardware and Architecture

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