Computational Extraction of Intonation and Tuning Systems from Multiple Microtonal Monophonic Vocal Recordings with Diverse Modes

This paper presents a computational methodology for analyzing intonation and deriving tuning systems in microtonal oral traditions, utilizing pitch histograms, Dynamic Time Warping (DTW), and optimization techniques, with a case study on a complete repertoire performed by a master of Iranian Classical Vocal Music (145 pieces). Pitch frequencies are extracted directly from vocal performances, and while alignment with MIDI notes is not a standard practice in our approach, we incorporate it where available, using DTW to refine interval analysis. By modeling intonation variations across multiple recordings, we derive structured tuning frameworks that capture both the flexibility of performance and the underlying systematic tendencies. Optimization techniques are applied to align intervals across the oral tradition repertoire, capturing the specific tunings and modal structures involved. Our methodology highlights the potential of computational techniques in advancing musicological and ethnomusicological research, offering a data-driven approach to defining tuning systems in microtonal vocal traditions.