Senior Theses Presentations

Thursday, May 25, 2017
Dartmouth Hall 206
4:30 pm - 6:30 pm

Maggie Baird
Title: "Variable word-final vowel reduction and deletion in Gurmancema: a maximum entropy model"
Gurmancema (Gur, Burkina Faso) displays an overall dispreference for word-final tense vowels phrase-medially. Repairs include vowel reduction and vowel deletion, which vary both across and within phonological contexts. This work will provide an overview of the complex data patterns and describe a weighted constraint approach to the data patterns using a Maximum Entropy Harmonic Grammar. Weighted constraints are preferred to ranked constraints due to variability in the data and to account for cases of constraint ganging, including superadditivity.

Corinne Kasper
Title: "Three Fires verbal morphology and grammatical description: implications for Potawatomi pedagogy"
Ojibwe, Odawa, and Potawatomi are three closely related, endangered Algonquian languages indigenous to the Great Lakes region. Potawatomi is my heritage language. It is from that perspective that this paper focuses heavily on analyzing and comparing the three languages for the purpose of language revitalization. This paper is split into three main sections: Comparative Algonquian, Potawatomi verbal morphological analysis, and grammatical leveling and extension. From there, the paper more fully discusses those pedagogical approaches by comparing Potawatomi to Odawa and Ojibwe for the purpose of understanding phonological restructuring and proposing language planning focusing on leveling.

Chaeyoon Kim
Title: "A large-scale online study of dialect variation in the US Northeast: Crowdsourcing with Amazon Mechanical Turk"
Description: New England has some of the most fine-grained dialect regions in North America, some of which trace back hundreds of years. Previous studies suggest that new dialect boundaries emerge along the same lines as previous generations. This study aims to (i) identify the current geographic boundaries of dialect features relative to those of previous generations and (ii) assess large-scale crowdsourcing methods via Amazon Mechanical Turk as an effective means to collect audio recordings for sociophonetic analysis. Such crowdsourcing methods can open up new doors for future linguistic researchers to greatly increase sample size and geographic range in an efficient manner.

Free and open to the public!