Spectral Analysis for Detecting Affective Variations in Arabic Speech

Authors

  • Tria Barkahoum

Keywords:

Speech-based emotion recognition; spectral audio analysis; natural language processing; Arabic speech; Mel-Frequency Cepstral Coefficients (MFCCs); machine learning.

Abstract

This study aims to explore the effectiveness of spectral audio analysis techniques for detecting emotionalvariations in spoken Arabic discourse. With the rapid advancement of human–machine interactions,understanding a speaker's emotional state has become a fundamental component of developing more intelligent and responsive systems.

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References

Al-Otaibi, K. (2022). Computational phonetics and Arabic dialects: A study of phonetic variation and its impact on automatic recognition systems. Academic Publishing House.

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Published

2025-11-24

How to Cite

Tria Barkahoum. (2025). Spectral Analysis for Detecting Affective Variations in Arabic Speech. Pegem Journal of Education and Instruction, 15(4), 2915–2923. Retrieved from https://www.pegegog.net/index.php/pegegog/article/view/4479

Issue

Vol. 15 No. 4 (2025): EARLY VIEW

Section

Article

License

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