2 Scopus citations

Abstract

One of the main foci of addiction research is the delineation of markers that track the propensity of relapse. Speech analysis can provide an unbiased assessment that can be deployed outside the lab, enabling objective measurements and relapse susceptibility tracking. This work is the first attempt to study unscripted speech markers in cocaine users. We analyzed 23 subjects performing two tasks: describing the positive consequences (PC) of abstinence and the negative consequences (NC) of using cocaine. We perform two main experiments: first, we analyzed whether acoustic and semantic features can infer clinical variables such as the Cocaine Selective Severity Assessment; then, we analyzed the main problem of interest: to see if these features are powerful enough to infer if the subjects remains abstinent. Our results show that speech features have potential to be used as a proxy to monitor cocaine users under treatment to recover from their addiction.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6391-6394
Number of pages4
ISBN (Electronic)9781479981311
DOIs
StatePublished - May 2019
Event44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
Duration: 12 May 201917 May 2019

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2019-May
ISSN (Print)1520-6149

Conference

Conference44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
Country/TerritoryUnited Kingdom
CityBrighton
Period12/05/1917/05/19

Keywords

  • abstinence
  • acoustic
  • cocaine
  • drug addiction
  • semantic

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