Early Seventeenth-Century Harmonic Practice: A Corpus Study of Tonality, Modality, and Harmonic Function in Italian Secular Song with Baroque Guitar Accompaniment in Alfabeto Tablature

• Other Authors: Tompkins, Daniel C. (authoraut)
• Format: Others
• Language: English; English
• Published: Florida State University
• Subjects: Music
• Online Access: http://purl.flvc.org/fsu/fd/FSU_2017SP_Tompkins_fsu_0071E_13798

This dissertation investigates harmonic propeties of Italian secular songs with Baroque guitar accompaniment in alfabeto tablature, which was a system of letters and other symbols that represented a chord shape to be strummed using all five courses. All of the resulting chords form major or minor triads. These letters were printed in songbooks for guitarists to accompany secular songs. This triadic accompaniment has significant implications for understanding harmonic practices during the seventeenth century. The purpose of this dissertation is to use computational methods to better understand the harmonic features of the alfabeto song repertoire, which can perhaps be a window through which we can understand the broader harmonic practices of secular genres in the early seventeenth century. Machine learning algorithms are employed to understand the modal framework and harmonic function of the alfabeto corpus. K-means clustering is used to determine how many modes are present within the corpus, building upon the recent work of Albrecht and Huron. To understand the harmonic function within the alfabeto corpus, hidden Markov models analyze the number of functions and which chords belong to each of those functions using a similar methodology to Quinn and White. The analyses also compare the alfabeto corpus to corpora of other genres and eras such as J.S. Bach, Palestrina, and Franco-Flemish composers. The alfabeto corpus is also compared with itself to better understand its style and any changes over time. This dissertation provides a fresh look at harmonic practice in the seventeenth century by using statistical models that are informed by historical performance practice. === A Dissertation submitted to the College of Music in partial fulfillment of the requirements for the degree of Doctor of Philosophy. === Spring Semester 2017. === March 6, 2017. === Baroque, Early Music, Guitar, Machine Learning, Music Theory, Tablature === Includes bibliographical references. === Evan A. Jones, Professor Directing Dissertation; Charles E. Brewer, University Representative; Clifton Callender, Committee Member; Jane Piper Clendinning, Committee Member.