Digital Approaches to Troubadour Song
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DIGITAL APPROACHES TO TROUBADOUR SONG Katie Elizabeth Chapman Submitted to the faculty of the University Graduate School in partial fulfillment of the requirements for the degree Doctor of Philosophy in the Jacobs School of Music, Indiana University January 2020 Accepted by the Graduate Faculty, Indiana University, in partial fulfillment of the requirements for the degree of Doctor of Philosophy. Doctoral Committee ______________________________________ Giuliano Di Bacco, Ph.D., Chair ______________________________________ Daniel Melamed, Ph.D. ______________________________________ Giovanni Zanovello, Ph.D. ______________________________________ Elizabeth K. Hebbard, Ph.D. December 13, 2019 ii Copyright © 2020 Katie Chapman iii For Grandmama iv Acknowledgements This dissertation would not have been possible without the support I received from individuals and groups at Indiana University and at other institutions. First, I would like to thank the four members of my committee for their ceaseless support, feedback, and conversations during this project. My thanks also go to Michael Long for his feedback on early drafts of this dissertation and to Wayne Storey for discussions of the sources and their transmission. I would also like to express my gratitude to Hans Tischler for his enthusiasm and encouragement in early discussion of the project and the continued support for and interest in my dissertation project from Alice Tischler. I am very grateful for the sources of funding I have received for this project. I would like to thank both the IU Jacobs School of Music and the IU Musicology department for support through a dissertation-year fellowship in 2017-2018 and for presentations at conferences. I would also like to recognize several organizations for support they provided for travel to presentations and workshops related to this project, including the Digital Musicology Strand of the Digital Humanities at Oxford Summer School (2017), the Clifford Flanigan Memorial Travel Grant (2017) through the IU Medieval Studies Institute, the Peter Burkholder and Doug McKinney Musicology Fund (2019), and the Music Encoding Conference (2019). I would also like to acknowledge the University Graduate School for their support through two Grant-in-Aid of Doctoral Research grants which supported elements of both my research and my digital project. I undertook two major archival research trips over the course of writing this dissertation. In 2013, I received funding through the A. Peter Brown Travel Fund to conduct my initial v manuscript research, during which I worked with troubadour sources at the Biblioteca Ambrosiana in Milan, the Biblioteca Marciana in Venice, the Biblioteca Riccardiana in Florence, and the Bibliothèque nationale de France in Paris. During a second archival trip in 2017, I received support from the American Musicological Society through their M. Elizabeth C. Bartlet Travel Grant; this permitted me to work with sources as the Biblioteca Ambrosiana, two different divisions of the Bibliothèque nationale de France in Paris, and the Biblioteca de Catalunya in Barcelona. I would also like to thank Ilaria Zamuner for her generosity in discussing my project during my first archival trip in 2013. I am very grateful to the staff of the archives I visited both for their assistance during my time at their institutions as well as in procuring images of manuscripts. I particularly wish to thank Friedrich Simader and Ingeborg Formann at the Österreichische Nationalbibliothek in Vienna for their assistance with obtaining images of the melodies in two manuscripts, Eug and Hoh, as neither manuscript is available for direct consult because of their current states of conservation. The digital humanities and computational components of this project would not have been possible without the assistance of several groups and individuals who provided expertise, feedback, and essential support and training in the various techniques I employ in this project. First, I must acknowledge my gratitude to Jan Koláček for graciously agreeing to help with the original installation of my database (the Troubadour Melodies Database created for this project), including use of his original Melody Search Tool module, as well as for allowing me to alter the existing tool. I would also like to thank Debra Lacoste, Jennifer Bain, and Susan Boynton for their feedback on the database. I am grateful to members of the Institute for Digital Arts and Humanities (IDAH) at Indiana University for both their technical support and conversations about the project over the years, particularly Kalani Craig, Mary Borgo Ton, Michelle Dalmau, vi and Daniel Story. I would also like to acknowledge the essential support I received through technical training offered by IDAH, the IU Scholar’s Commons, IT Training, and Research Technologies while at IU. These organizations provided both training and consultations in the planning stages of the project as I learned to use new software and drafted plans for the database, as well as helping refine the project in later stages. In particular, I am deeply grateful for the support of members of the Cyberinfrastructure for Digital Humanities and Creative Activities, with whom I have had the privilege of working during the last few years. They, along with other staff in Research Technologies, have been enormously supportive as I finished this dissertation. Tassie Gniady has been a constant source of support for my project, including connecting me with the consultants who assisted me with the additions to the Melody Search Tool, Adam Hochstetter and Guangchen Ruan. David Kloster provided support for the text analysis components of my dissertation, particularly for the Python script I use for Latent Semantic Analysis (LSA). I would also like to acknowledge the Indiana University Pervasive Technology Institute for providing HPC (Carbonate) resources that contributed to the results reported within this project. This research was thus also supported in part by Lilly Endowment, Inc., through its support for the Indiana University Pervasive Technology Institute. Finally, I am forever grateful to my friends and colleagues for their contributions in so many ways throughout this project. I could not have made it through this process without their emotional support and their willingness to read drafts, discuss problems, and listen to practice runs of papers and presentations. I would also like to thank my family for their love and support during this process. vii Katie Elizabeth Chapman DIGITAL APPROACHES TO TROUBADOUR SONG The troubadours were poet-composers who flourished in Occitania (today southern France) and surrounding areas during the twelfth and thirteenth centuries. Their lyric poems survive in chansonniers (songbooks) which usually contain only the texts. A fraction of the melodies that accompanied these poems were written down; fewer than 350 melodies survive for a lyric corpus of over 2,600 songs which appear over 13,000 times in all extant sources. This dissertation is part of a larger project whose aim is twofold: to create an open- access, electronic, searchable archive of these melodies and to apply computational methods of analysis to identify the musical characteristics of the melodies, find patterns and relationships, and track trends in style both over time and within the works of individual authors. In this study, I first illustrate the methodology I followed to assess and encode the corpus of troubadour melodies and give an overview of the types of tools used to analyze the encoded melodies. In the subsequent chapters, I present five case studies which investigate musical features of the repertory through computational and statistical approaches, where I confirm, revise, or expand on existing knowledge of the repertory. The first case study identifies the extent and features of Guiraut Riquier’s melismatic writing by applying analytical techniques typically used to analyze textual corpora. The second case study applies a different technique borrowed from computational linguistics, Latent Semantic Analysis (LSA), to track the similarity of melodies with versions extant in multiple sources and to compare the phrases of melodies in one manuscript which have notation for more than one stanza. The three case studies in Chapter III adopt other analytical approaches to investigate and compare the pitch and interval viii content of the melodies. These studies help identify patterns in pitch organization in the entire repertory, point out stylistic trends of specific troubadours, and compare selected musical features by source. Overall, this study demonstrates the possibilities of computational approaches to contribute to existing scholarship on this repertory. Furthermore, the digital archive created for this project aims to empower additional research on the music of the troubadours, including the study of corpus-wide characteristics, the analysis of stylistic traits in specific authors or sources, and changes in style over the course of the tradition. ______________________________________ Giuliano Di Bacco, Ph.D., Chair ______________________________________ Daniel Melamed, Ph.D. ______________________________________ Giovanni Zanovello, Ph.D. ______________________________________ Elizabeth K. Hebbard, Ph.D. ix Table of Contents Acknowledgments v Abstract viii List of Figures xi List of Musical Examples xiii Manuscript Sigla xiv Introduction 1 I. Technical Description and Methodology 27 II. Text Analysis Tools 81 Case Study 1: Melismas