ARTIFICIAL INTELLIGENCE AND THE EVOLUTION OF MUSICAL INTONATION
DOI:
https://doi.org/10.29121/shodhkosh.v7.i1s.2026.7139Keywords:
Artificial Intelligence, Musical Intonation, Pitch Correction, Machine Learning, Audio Signal Processing, Context-Aware Models, Real-Time Feedback, Singing Voice Synthesis, Human-AI CollaborationAbstract [English]
Intonation, the accuracy of pitch and tone, is a critical component of music that deeply influences harmony, emotional expression, and the listener's perception of a performance. With recent advancements in artificial intelligence (AI), new methods have emerged to analyze and enhance musical intonation with unprecedented precision. This paper explores state-of-the-art approaches for AI-enhanced intonation, including context-aware machine learning models, real-time performance monitoring systems, and deep generative models for natural-sounding pitch correction. (Wager et al.; Hai and Elhilali; Zhuang et al.) Techniques such as audio signal analysis, machine learning-based pitch prediction, real-time feedback loops, automatic pitch correction algorithms, and musical context-awareness are examined in terms of their methodology and effectiveness. We review studies demonstrating significant improvements in intonation using AI-based systems, and discuss how even minor pitch deviations - which can detract from the quality and emotional impact of music - can be automatically detected and corrected. (Wager et al.; Pardue and McPherson) AI-enhanced intonation systems have the potential to revolutionize music production, live performance, and education by providing musicians and producers with intelligent tools that preserve the expressive nuance of the original performance while improving technical accuracy. (Hai and Elhilali; Zhuang et al.) We also address the challenges facing this field, such as the need for high-quality training data and the handling of complex musical nuances. The paper concludes with future directions, envisioning more sophisticated, context-aware AI models that integrate musical knowledge (e.g., genre, timbre, and phrasing) for truly human-like intonation adjustment.
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Copyright (c) 2026 Rishpal Singh Virk , Amanneet Kaur Arora, Kumkum Bala, Dr.Sarika N.Patil, Gurpreet Kaur, Prof.Sharayu S.Sangekar
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