Guilherme D. Garcia began teaching linguistics at BSU in January. A native of Brazil, Prof. Garcia has a PhD from McGill University in Montreal. He specializes in Phonology and Phonetics, both of which focus on the speech sounds that make up languages. Among other things, his research focuses on how speakers learn pronunciation patterns and how meter–the sequences of weak and strong syllables–contrast in different languages. Beyond linguistics and teaching, Prof. Garcia is passionate about guitars and photography. In this interview, he talks about his current research, about avoiding biases, and about his role models.
How would you describe your teaching perspective?
I think that the most important skill a student can acquire these days is critical thinking, and that’s the underlying objective of my classes. Once you learn how to filter all the information available, you can be sufficiently autonomous to build your own path in a particular field of study. Since I teach theoretical and experimental linguistics, I often emphasize that our conclusions about a particular theoretical framework should be guided by the data available—and not by our subjective biases towards a particular theory. One important question to ask when we examine linguistic data is whether a different explanation could also account for the patterns we observe. Naturally, that question should be considered outside the classroom as well.
Who are your biggest role models?
My parents taught me all those things you don’t learn at school. Most of everything else I learned from amazing professors and my wife. My PhD supervisor is certainly my academic role model.
Tell us a little about your current projects.
Right now I’m working on a couple of things. I have a paper under revision on whether or not we can generalize patterns in our language which may be inconsistent with what’s observed cross-linguistically (I’ll present this paper at the 41st annual GLOW conference, held in Budapest this year). I have another paper under way (joint work) that compares English and Portuguese, and argues that even though these languages look very similar in terms of their metrical structure, they are actually fundamentally different. I’m also working on an upcoming presentation in Chicago where I show that a Bayesian approach to data analysis can be particularly useful in the study of Second Language Acquisition. Finally, I’m working with some researchers at McGill University on two projects: one that investigates how prosodic factors can affect how we interpret pronouns in Italian, and one that examines how patterns of vowel deletion in Quebec French can help us better understand the underlying metrical pattern(s) in the language. This project was recently presented at the Annual Meeting of the Linguistic Society of America, held in Salt Lake City this past January.
How did you decide on the work you are focusing on now?
I’m curious to see how we can acquire and generalize subtle aspects of our native (or second) language. By “subtle,” I mean facts about language that we don’t really know exist in speakers’ grammars, but which emerge in carefully designed experiments. This can help us better understand how powerful our language acquisition mechanism is at learning and generalizing linguistic patterns. In the context of second language acquisition, this can help us identify with precision underlying differences between native speakers and second language learners. I also really enjoy analyzing language data and assessing how accurate standard assumptions are given what we actually observe. So my research connects these two worlds: data analysis and linguistics (phonology).