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by IQAC KIITKIIT Deemed to be University — Internal Quality Assurance Cell

Publication2025

Enhancing Turkish Music Emotion Prediction: A Comparative Analysis of Machine Learning Techniques

The record

Type
Publication
Date
1 January 2025
Level
International — held abroad
Journal
Communications in Computer and Information Science
Volume
2243 CCIS
Pages
43-52
Published
1 January 2025
DOI
10.1007/978-3-031-81369-6_4
Scopus ID
85219202566
ISSN
18650929
Authors
5
Open access
No
Citations
0
International co-authorship
Yes
Co-author countries
IN, US

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

  1. 9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending

    TargetPrimaryHigh confidenceJudged

    Applies stacking and voting machine learning classifiers for Turkish music emotion recognition achieving 93% accuracy across happy, sad, angry and relax categories.

    High confidence
    The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
    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

  2. 17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing

    TargetSecondaryHigh confidenceRule-derivedrule sdg17-structural-v1

    Structural signal: co-authorship outside India.

    Rule-derived
    Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
    Produced by
    sdg17-structural-v1, under kortex-publication-v1

Viksit Bharat @2047

  1. vb-3.2 Digital technology and artificial intelligence

    Sub-themePrimaryHigh confidenceJudged

    Advances artificial intelligence research through multi-model classifier methodology for cultural content analysis and emotion prediction.

    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

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KIIT Deemed to be University. “Enhancing Turkish Music Emotion Prediction: A Comparative Analysis of Machine Learning Techniques”. Kortex.

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