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This paper investigates whether artificial intelligence-generated music (AIGM) can match human-composed music in emotional expression. By comparing listener responses to Japanese pop music clips across four conditions: AI/human and vocal/instrumental, this study examines emotion perception, authorship identification, and the role of lyrics. Results show that participants struggle to distinguish AI from human music, but consistently rate human compositions as more emotionally intense. Vocal presence and songs rated as happy are more easily recognized and emotionally impactful than instrumental or sad tracks. Findings highlight both the strengths and current limitations of AIGM in emotional communication.

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Can AI Capture Emotion? A Study on Human Emotional Perception and Response to AI-Generated and Human-Composed Pop Music

  • 会议论文

  • 发表日期：

    2026年

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  • Lucy Chen,
  • KC Collins

摘要

This paper investigates whether artificial intelligence-generated music (AIGM) can match human-composed music in emotional expression. By comparing listener responses to Japanese pop music clips across four conditions: AI/human and vocal/instrumental, this study examines emotion perception, authorship identification, and the role of lyrics. Results show that participants struggle to distinguish AI from human music, but consistently rate human compositions as more emotionally intense. Vocal presence and songs rated as happy are more easily recognized and emotionally impactful than instrumental or sad tracks. Findings highlight both the strengths and current limitations of AIGM in emotional communication.