Publication2023
Speech emotion recognition by using complex MFCC and deep sequential model
- Industry, Innovation and Infrastructure
- Innovation, Science and Technology
The record
- Type
- Publication
- Date
- 1 March 2023
- Level
- National
- Journal
- Multimedia Tools and Applications
- Volume
- 82
- Issue
- 8
- Pages
- 11897-11922
- Published
- 1 March 2023
- DOI
- 10.1007/s11042-022-13725-y
- Scopus ID
- 85137867132
- ISSN
- 13807501
- Authors
- 1
- Open access
- No
- Citations
- 58
- 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
Research develops novel deep sequential model for speech emotion recognition using complex MFCC features, advancing machine learning methodology for audio signal classification.
- 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 Innovation, Science and Technology
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 9 label. Research develops novel deep sequential model for speech emotion recognition using complex MFCC features, advancing machine learning methodology for audio signal classification.
- 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 by using complex MFCC and deep sequential model”. Kortex.