RESEARCH LABORATORIES
UF’s Linguistics Department has a number of laboratories to enable to conduct research from behavioral linguistic research to neuroscience and computational research. UF Linguistics hosts a phonetics/phonology lab, two EEG labs to look at brain waves in real time while speakers are processing linguistic information, and labs to analyze linguistic data computationally. You can find a description of the labs here below!
- Brain, Language and Bilingualism Laboratory
- Corpus Linguistics Laboratory
- Language Documentation Laboratory
- Language over the Lifespan Laboratory
- Speech, Lexicon and Modeling Laboratory
- Computational Linguistics Laboratory
- Machine Learning for Endangered Language Documentation Laboratory
Brain, Language and Bilingualism Laboratory
The Brain and Language Lab is headed by Dr. Eleonora Rossi (Eleonora.rossi@ufl.edu) and Dr. Edith Kaan (kaan@ufl.edu). The Rossi Lab research team investigates how bilingualism shapes the mind and the brain, with a focus on understanding neural changes that occur at the earliest stages of new language acquisition. The Rossi Lab Team works with behavioral, and EEG data to track real-time brain responses. The Kaan Lab research team conducts experiments to investigate language processing in the brain. In particular, the lab is interested in how humans process (a) sentences and texts, (b) lexical tones, and (c) language in the context of second-language learning. A variety of experimental techniques are employed, including questionnaires, reading studies, and event-related brain potentials (ERPs).
Corpus Linguistics Laboratory
The Corpus Linguistics Lab is headed by Dr. Stefanie Wulff (swulff@ufl.edu). Its researchers investigate language data using corpora. Corpora are large-scale digital collections of language. The lab offers access to various corpora of English, German, Spanish, and other languages; corpora of written and transcribed spoken language; and various specialized corpora such as corpora of academic speech and writing, learners of English as a second language, and the like. Access to these corpora is provided using various software tools such as AntConc, MonoConcPro, WordSmith Tools, and R. The lab also provides access to Eprime for experiments.
In the UF Corpus Linguistics Lab, corpus linguistics is a method, not a theory. All faculty and students affiliated with the Corpus Linguistics Lab are united by their commitment to rigorous, empirical analyses of language data. Correspondingly, the researchers affiliated with our lab conduct research in various theoretical frameworks and on a wide range of topics, including language processing, second language acquisition, and the synchronic and diachronic description of languages such Dutch, English, Spanish, and many others.
Language Documentation Laboratory
The Language Documentation Lab is overseen by Drs. Aaron Broadwell (broadwell@ufl.edu), James Essegbey (essegbey@ufl.edu), Brent Henderson (bhendrsn@ufl.edu), and Fiona McLaughlin (fmcl@ufl.edu). It provides space for faculty and students involved in the documentation and analysis of understudied, minority, and endangered languages. There is a soundproof booth for phonetic studies as well as computing equipment for on-going documentation projects. The lab also has audio and video equipment that can be borrowed.
Language over the Lifespan Laboratory
The Language over the Lifespan (LOL) lab is headed by Dr. Lori Altmann (laltmann@ufl.edu). The LOL Lab at UF investigates the relationship between memory and language use in adults. We study young and older adults with normal and impaired language. The lab is located in the basement of historic Dauer Hall, on the northern edge of the UF campus. The LOL lab has dedicated parking spaces just behind Dauer Hall for easy access. While most of the testing is done on campus, the lab is also equipped to travel! Healthy older adults and Alzheimer patients are often tested at their own homes.
Current on-site projects examine language use in adults with Alzheimer Disease and adults with dyslexia. What do dyslexia and Alzheimer disease have in common? Both disorders are associated with differences in the parts of the brain used for language. In dyslexia, these differences are there at birth and affect the way language is processed throughout life. In Alzheimer disease, these differences are degenerative changes that affect an already well-trained language system. Surprisingly, the effects of these two disorders on language use can be quite similar.
Current projects include: Language and Memory in Dyslexic Adults, Typicality Effects on Alzheimer’s Naming, Sentence Production and Comprehension in Healthy Adults, and Concept Combination in Dementia.
Speech, Lexicon and Modeling Laboratory
The Speech, Lexicon and Modelling (SLaM) lab at UF is dedicated to advancing applied and theoretical research involving spoken speech and grammar (phonetics and phonology) and word knowledge (lexicon). The SLaM lab is also home to our work in Computational Linguistics (for more information, click here).
SLaM is co-directed by Dr. Kevin Tang, Dr. Ratree Wayland and Dr. Caroline Wilshire at UF Linguistics. It provides research opportunities for undergraduate and graduate students. We welcome curious and motivated UF students from a wide range of disciplines (from Engineering to Digital Humanities) to join us. Find out more at https://slam.lin.ufl.edu/
Wanna be a SLAMer? Please see what opportunities are available here. For more information, please contact Dr. Kevin Tang. Location: 4017 Turlington Hall (tang.kevin@ufl.edu).
Computational Linguistics Laboratory
The Computational Linguistics Lab is headed by Dr. Zoey Liu. The lab studies variation/generalization across languages and machines. Broadly, we are interested in questions relevant to language typology, language learning as well as multilingual natural language processing. For instance, to what extent do languages with different grammatical characteristics demonstrate structural variation, and why would that be? How would variation in parent input affect production variation produced by children in their early language development? How well do computational models generalize across languages and what are better ways to evaluate variation in their performance? We address these questions with a data-driven approach, methods of number counting at varying degrees of carbon dioxide consumption, along with a non-western mind. https://ufcompling.github.io/
Machine Learning for Endangered Language Documentation Laboratory
The Machine Learning for Endangered Language Documentation (MELD) Laboratory is headed by Dr. Sarah Moeller. It is dedicated to the advancement of natural human language technology, the documentation and description of languages from a computational perspective, and a richer and more accurate representation of all the world’s 7000+ languages in all fields related to artificial intelligence (AI).