About

SongHelix would not be possible without the help of many, many people. We would like to acknowledge and thank all of them here.

Director
Seth Keeton, DMA

Grants from:
The University of Utah, University Research Committee
The University of Utah, Research Incentive Seed Grant Program

Advisory Board
Editorial Board

Website and database designer
Rachel O’Connor

McKay Music Library Director

Researcher and Major Contributor
Jacquelyn Matava, DM

Research assistants
Amy Livingston
Garrett Medlock, thanks to the McKay Music Library
John Olshinski, thanks to the McKay Music Library
Jonathon Comfort
Kahli Dalbow

There has never been a simple way to search through the vast number of art songs by poet, date of composition, thematic links, keywords, or utility. SongHelix brings this ever-evolving information available into one searchable location. It is an online tool that enables users to search through the vast repertoire of art songs in order to find just the right piece. The website’s immediate purpose is to give singers and teachers the primary online tool for finding related repertoire. A secondary, and broader purpose will be to help to revitalize the form of voice recital by allowing for creative programming through novel associations.

The website makes it possible for the user to search song repertoire by terms customarily found in print reference, but SongHelix’s real power is the ability to search by “Feature” as well. When searching within the “Feature” category the user will be able to discover aspects of the songs such as: dreams, stages of life, moving water, Greek mythology, particular metaphors, etc.

We anticipate that the website’s primary users will be voice teachers at all levels (pre-college, undergraduate and graduate), voice students, collaborative pianists, and professional singers.  Our tool will also benefit song composers and DMA voice students and musicologists. Currently composers expend time and energy in becoming discovered or remaining relevant. With modern composers’ inclusion in the dataset, their music will be discovered alongside those of the great masters of the past. Additionally as the dataset grows, gaps in song scholarship become apparent. These gaps are ideal for catalyzing new research in the field for faculty or doctoral students’ lecture recitals or theses.