Synthia Pullum, M.M. New England Conservatory
Ian Howell, D.M.A. New England Conservatory, M.Mus. Yale University, Voice Faculty and Vocal Pedagogy Director New England Conservatory
This project was presented in Boston on 27 April 2014 in partial fulfillment of the M.M. in Vocal Pedagogy at the New England Conservatory. The authors wish to thanks Alberto Pacheco for both creating this analysis method, and also encouraging others to use it.
When training young classical singers, teachers must assign repertory that respects their tessitura, or average comfortable singing range. As the voice matures, this tessitura will shift due to both training and the aging process, and many singers change their repertory over the course of their career. In this pilot study, we chose six arias from roles Ms. Leontyne Price sang over the course of her career. By applying a method of statistical analysis developed by Alberto Pacheco, we were able to define the approximate tessitura of each aria. While neither a comprehensive assessment of her voice, nor thorough analysis of her repertory, when placed in chronological order according to the year Ms. Price debuted the role (and, one would assume, the year she felt capable of performing the role), these data begin to suggest the way in which her voice may have changed over time.
Pacheco developed a method of statistical analysis enabling one to define the tessitura of a given work (plus upper and lower extensions) by graphically displaying the frequency of occurrence of each pitch according to the lowest common denominator rhythm. For example, if eighth notes are the shortest unit of measure, a half note on a G4 would contribute four eighth notes to that pitch’s total value. Whichever pitch occurs most frequently helps define the boundaries of the tessitura. Any pitch occurring half (or more) as frequently as the most frequent pitch is considered within the tessitura. E.g. if G4 occurs forty times, any pitch occurring twenty or more times in the piece is within the tessitura. The highest and lowest pitches within this range are considered the low and high boundaries of the tessitura. Any pitches above or below are considered extensions. Pacheco’s method accounts for tempo variations inherent in music: sections with different tempi are analyzed separately (short sections are discarded); small variations in tempo are not taken into account; and “recitatives, cadenzas, grupetti, [and] appoggiaturas…” are not considered. While these graphs are only approximations, they are sufficiently detailed to give a general sense of the tessitura of each piece.
While this pilot study was limited to seven samples from six arias, the results nonetheless point to the value of Pacheco’s method. We conclude that Ms. Price’s tessitura likely expanded in her mid career, and then gradually lowered as her voice matured (see figure 1 and the supporting graphs). Though care was taken to select representative arias from each opera, a more thorough study—averaging all the music from each role—is warranted to confirm our conclusions. Ms. Price likely had a long and successful career in part because she chose repertory that showcased her strengths—rather than overextended her voice—for each specific period of her performing career.
 Alberto Pacheco, “Angelica Catalini’s Voice According to a Method of Statistical Analysis,” Journal of Singing 69, 5 May/June (2013): 557-567.
 Pacheco, 558.