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Musicolinguistics: New Methodologies for Integrating Musical and Linguistic Data
- Sleeper, Morgan Thomas
- Advisor(s): Gordon, Matthew
Abstract
Linguists have long examined language in musical contexts, just as ethnomusicologists have considered the language(s) of the musics they study. Though an increasing number of scholars are now combining (ethno)musicological and linguistic approaches in their work, this is still far from the norm in linguistics, where musical elements are often disregarded in analyses of language in musical context. This dissertation aims to challenge this status quo, by introducing and demonstrating new methodologies for integrating musical data into linguistic analyses in three subfields: structural linguistics, sociocultural linguistics, and language revitalization.
Each new method is illustrated through a representative study. In the first, I introduce a novel method for integrating musical transcription into language documentation using ABC notation in ELAN, which reveals a striking correspondence between lexical tone and musical melody in Tlahuapa Tù'un Sàví, a Mixtec language spoken in Guerrero, Mexico. In the second, I present a multimodal discourse analytic method for sociocultural linguistic research, and use it to show how three different Welsh rock artists enact diverse identities through co-temporal code-switching and musical style-shifting. In the third, I demonstrate how linguists can combine musical and linguistic data to create an UTAUloid — a combination speech and music synthesizer for collaborative vocal songwriting — to aid in musical language revitalization efforts, through an example in Cherokee.
Together, the results of these studies illustrate the rich potential of music in linguistic research across subfields, and show that the combination of musical and linguistic data yields unique analyses not possible by examining language alone. More than optional accompaniment, music is an essential component of a discourse functional approach to language in musical contexts, and the methodologies introduced in this dissertation aim to make including musical data as accessible as possible.
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