Plural Allomorphy in Kadiwéu

• Grant number: 23/13489-0
• Support Opportunities: Scholarships in Brazil - Master
• Start date: March 01, 2024
• End date: February 28, 2026
• Field of knowledge: Linguistics, Literature and Arts - Linguistics - Linguistic Theory and Analysis
• Principal Investigator: Maria Filomena Spatti Sandalo
• Grantee: Leo Vitor Navarro
• Host Institution: Instituto de Estudos da Linguagem (IEL). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated scholarship(s): 25/03673-3 - MaxEnt and the Allomorphy of Plural in Kadiwéu: Internship at UMass Amherst, BE.EP.MS

Abstract

This research endeavors to delve into the intricacies of plural allomorphy in Kadiwéu (a brazilian indigenous language), which is characterized by the presence of nine distinct allomorphs in its pluralization process. The primary objective of this study is to gain a comprehensive understanding of the mechanisms governing the plural form and to anticipate its allomorphy, while accounting for three potential determinants: prosodic, semantic, and phonological-segmental factors. The prosodic factor highlights the impact of stress on plural formation, the semantic factor explores the influence of word semantics, and the phonological-segmental factor scrutinizes the role of morphophonological word structure. The study corpus comprises 1590 data points, categorized into nouns and adjectives. The initial phase of the research methodology entails the audio recording of the collected corpus, aided by a native Kadiwéu speaker. Subsequently, the recorded data will undergo analysis through the Praat software, with the aim of discerning any prospective prosodic correlations pertaining to the allomorphy. The second phase of the methodology will involve an experiment in the form of a wug test. This experiment is constituted by nonce words, artfully devised on the basis of phonological-segmental variables (such as place of articulation and tonic stress) and semantic variables (such as animacy and humanness attributes). Prior to the experiment's execution, these nonce words will be subjected to a rigorous naturalness assessment to filter out any unnatural data (according to the native speaker's intuition). The ensuing dataset will be analyzed based on Optimality Theory, specifically according to the Maximum Entropy Grammar model. This approach seeks to unravel the overarching principles governing plural forms and their inherent lexical tendencies. Ultimately, data modeling will be conducted using the MaxEnt Grammar Tool statistical software, adept at generating a grammar of constraints and offering probabilistic insights into the likelihood of occurrence for each constituent element.