Research Spotlight Lunches
Come for research, stay for lunch! At our well-loved Research Spotlight Lunches, faculty from all over campus (and this year, even beyond!) share exciting new advances in their work.
Lunch is served at 12:15 pm, talks take place 12:30-1:45 (including audience questions).
Abstracts and titles tbd.
Monday, January 9
Naomi Feldman (LING, CS): How phonetic learners should use their input
Children have impressive statistical learning abilities. In phonetic category acquisition, for example, they are sensitive to the distributional properties of sounds in their input. However, knowing that children have statistical learning abilities is only a small part of understanding how they make use of their input during language acquisition. Using computational models, I consider three basic assumptions that go into statistical learning theories: the structure of learners' hypothesis space, the way in which input data are sampled, and the features of the input that learners attend to. Modeling results show that although a naïve view of statistical learning may not support robust phonetic category acquisition, there are several ways in which learners can potentially benefit by leveraging the rich statistical structure of their input.
Vivian Sisskin (HESP): The Atypical Disfluency Project
Treatment protocols have been described for stuttering and other fluency disorders including cluttering and language-based disfluency. However, case studies reveal atypical disfluency characterized by final part-word repetition (“rhyme repetition”), or atypical pausing and phrase repetition. Symptoms have been observed among individuals with autism spectrum disorder as well as among neurotypical individuals. Our goal is to better understand features of atypical disfluency, its accompanying behaviors, and its response to traditional stuttering therapy.
Michelle Morrison (CASL): It’s not easy being green: creative use of noun class prefixation for both semantic and reference tracking purposes
Bantu languages are notorious for their noun class systems. Under traditional analyses, nouns are assigned to a particular class, which is (usually) indicated via a noun class prefix. A noun will then trigger concordial agreement on other elements in a construction, including verbs, adjectives, and demonstratives. Instances where the noun class stem appears with a noun class marker that does not correspond to the noun stem's supposed class are considered to be derivation, with fairly tight limitations on which noun class derivations are possible. Research on the Bantu noun class system has primarily focused on the form of noun class prefixes themselves, agreement patterns, and possible semantic motivation for individual classes. Much less attention has been paid to the functions of the noun class system, particularly with respect to its role within linguistic discourse. While many scholars recognize that noun classes are at least partially semantically motivated and that they play a role in reference tracking, the complexities of the interactions between these two functions and the ways speakers may manipulate the noun class system creatively within discourse has largely been ignored.
In this talk, I focus on Bena (a Bantu language spoken in southern Tanzania) and demonstrate that noun class membership seems to be more fluid than is traditionally thought. In fact, speakers can manipulate the noun class system for a number of different purposes, including reference tracking and participant disambiguation, stylistic and connotative expression, and even as a pragmatic strategy to indicate a shift in character voice. I will also discuss the importance of using different methodologies in linguistic fieldwork, and the complementary nature of elicitation-based strategies with more stimulus-based and corpus-driven approaches.
Jan R. Edwards (HESP): Dialect mismatch and its implications for academic achievement
Bill Idsardi (LING, UMD) and Jeff Heinz (LING, U Delaware): Personal Perspectives on Computational Linguistics
In this lunch talk we will survey some aspects of computational linguistics, but from a personal perspective. This will mainly consist of drawing distinctions between various practices in computational linguistics (especially computational phonology) along the following dimensions:
- Data vs. simulation vs. proofs
- Choice of model/benchmark/criteria for complexity, learning, ...
- Knife-edge between triviality and impossibility
- Tradeoffs between representations and computational power
- Mismatch between abstract models and the theoretical ontologies
Vessela Valiavitcharska (ENGL): Figures of Speech as Structures of Inference in Medieval Rhetorical Instruction
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