Improving speech depression detection using transfer learning with wav2vec 2.0 in low-resource envir...
Improving speech depression detection using transfer learning with wav2vec 2.0 in low-resource environments
About this item
Full title
Author / Creator
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
Formats
Publication information
Publisher
London: Nature Publishing Group UK
Subjects
More information
Scope and Contents
Contents
Depression, a pervasive global mental disorder, profoundly impacts daily lives. Despite numerous deep learning studies focused on depression detection through speech analysis, the shortage of annotated bulk samples hampers the development of effective models. In response to this challenge, our research introduces a transfer learning approach for de...
Alternative Titles
Full title
Improving speech depression detection using transfer learning with wav2vec 2.0 in low-resource environments
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_c2e538831aea4c27a34d447161b1167e
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_c2e538831aea4c27a34d447161b1167e
Other Identifiers
ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-024-60278-1
