Literature DB >> 29276807

DAVE: Detecting Agitated Vocal Events.

Asif Salekin1, Hongning Wang1, Kristine Williams2, John Stankovic1.   

Abstract

DAVE is a comprehensive set of event detection techniques to monitor and detect 5 important verbal agitations: asking for help, verbal sexual advances, questions, cursing, and talking with repetitive sentences. The novelty of DAVE includes combining acoustic signal processing with three different text mining paradigms to detect verbal events (asking for help, verbal sexual advances, and questions) which need both lexical content and acoustic variations to produce accurate results. To detect cursing and talking with repetitive sentences we extend word sense disambiguation and sequential pattern mining algorithms. The solutions have applicability to monitoring dementia patients, for online video sharing applications, human computer interaction (HCI) systems, home safety, and other health care applications. A comprehensive performance evaluation across multiple domains includes audio clips collected from 34 real dementia patients, audio data from controlled environments, movies and Youtube clips, online data repositories, and healthy residents in real homes. The results show significant improvement over baselines and high accuracy for all 5 vocal events.

Entities:  

Year:  2017        PMID: 29276807      PMCID: PMC5736321          DOI: 10.1109/CHASE.2017.47

Source DB:  PubMed          Journal:  IEEE Int Conf Connect Health Appl Syst Eng Technol


  6 in total

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Authors:  Margaret C Sewell; Xiaodong Luo; Judith Neugroschl; Mary Sano
Journal:  Int Psychogeriatr       Date:  2013-05-02       Impact factor: 3.878

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Authors:  Kristine N Williams; Yelena Perkhounkova; Ruth Herman; Ann Bossen
Journal:  Gerontologist       Date:  2017-08-01
  6 in total
  1 in total

1.  A Weakly Supervised Learning Framework for Detecting Social Anxiety and Depression.

Authors:  Asif Salekin; Jeremy W Eberle; Jeffrey J Glenn; Bethany A Teachman; John A Stankovic
Journal:  Proc ACM Interact Mob Wearable Ubiquitous Technol       Date:  2018-06
  1 in total

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