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Publication Date

2020

First Advisor

Katherine M. Kinnaird

Document Type

Honors Project

Degree Name

Bachelor of Arts

Department

Statistical and Data Sciences

Keywords

Data science, Machine learning, Music, Music information retrieval, Twang, Country music, Music genre, Statistical analysis

Abstract

Vocal twang, the sound created when emphasizing nasal vocals, is an omnipresent feature of American Country music, but remains under-studied in Music Information Retrieval. In this paper, I draw upon singer-detection research to explore whether twang is captured by timbre. I generate a dataset of representative American Folk and Country music, assess multiple ground truth sets for this data, and statistically analyse the relationship the relationship between twang and various timbral features. I find that twang has a significant relationship with timbre, but more studies must be conducted before it can be reliably predicted with machine learning techniques.

Rights

2020 Jessica Nichole Keast. Access limited to the Smith College community and other researchers while on campus. Smith College community members also may access from off-campus using a Smith College log-in. Other off-campus researchers may request a copy through Interlibrary Loan for personal use.

Language

English

Comments

xii, 138 pages : illustrations (some color) Includes bibliographical references (pages 135-138)

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