Publication2021
Detection of COVID-19 from speech signal using bio-inspired based cepstral features
The record
- Type
- Publication
- Date
- 1 September 2021
- Level
- National
- Journal
- Pattern Recognition
- Volume
- 117
- Published
- 1 September 2021
- DOI
- 10.1016/j.patcog.2021.107999
- Scopus ID
- 85104925416
- ISSN
- 00313203
- Authors
- 4
- Open access
- No
- Citations
- 70
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
3 Ensure healthy lives and promote well-being for all at all ages
Bio-inspired signal processing features for COVID-19 detection from speech signal develops non-invasive diagnostic tool for pandemic disease identification.
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-3.2 Digital technology and artificial intelligence
Speech-based disease detection technology represents innovative digital health tool application.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- 1
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Citing this record
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KIIT Deemed to be University. “Detection of COVID-19 from speech signal using bio-inspired based cepstral features”. Kortex.