Publication2023
Speech emotion recognition using multimodal feature fusion with machine learning approach
The record
- Type
- Publication
- Date
- 1 November 2023
- Level
- National
- Journal
- Multimedia Tools and Applications
- Volume
- 82
- Issue
- 27
- Pages
- 42763-42781
- Published
- 1 November 2023
- DOI
- 10.1007/s11042-023-15275-3
- Scopus ID
- 85153276727
- ISSN
- 13807501
- Authors
- 4
- Open access
- No
- Citations
- 63
- International co-authorship
- No
- Co-author countries
- IN
Classification
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UN Sustainable Development Goals
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Multimodal feature fusion combining MFCC, ZCR and spectrograms with machine learning achieves 99.64% speech emotion recognition accuracy
- 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
Artificial intelligence research advances emotional state recognition technology through advanced audio signal processing and machine learning methods
- 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. “Speech emotion recognition using multimodal feature fusion with machine learning approach”. Kortex.