Affiliations: | 2008-2012 | Linguistics/Psychology | Michigan State University, East Lansing, MI |
| | 2012-2017 | Neuroscience and Cognitive Science | University of Maryland, College Park, College Park, MD |
| | 2017-2020 | Speech, Language, and Hearing Sciences | University of Connecticut, Storrs, CT, United States |
| | 2020- | Communicative Disorders and Sciences | State University of New York, Buffalo, Buffalo, NY, United States |
Area:
speech perception, categorization, psycholinguistics
Website:
http://www.acsu.buffalo.edu/~ccheffne/
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High-probability grants
According to our matching algorithm, Christopher C. Heffner is the likely recipient of the following grants.
| Years |
Recipients |
Code |
Title / Keywords |
Matching
score |
| 2017 — 2018 |
Idsardi, William [⬀]
Newman, Rochelle (co-PI) [⬀]
Heffner, Christopher (co-PI) [⬀] |
N/AActivity Code Description:
No activity code was retrieved: click on the grant title for more information |
Doctoral Dissertation Research: Categorization and Segmentation Inside and Outside Language @ University of Maryland College Park
Humans hear the speech of others almost every day. Understanding that speech is often quite difficult, as can be seen when interacting with automated speech recognition technologies. Doing so requires the use of complex yet surprisingly effective cognitive abilities. But are the mental tools that humans use to understand speech used for speech only, or are there ones that are applied to multiple purposes? This project seeks to link language learning and perception to other tasks to determine the extent to which speech perception shares an underlying basis with other cognitive processes. This project will enrich the understanding of cognition. Furthermore, it could open up new avenues for designing technologies to better improve speech processing as well as lead to new methodologies to train people learning a second language.
To study the domain-specificity of speech perception, this project will center on two particular aspects of speech: category learning and segmentation. Accurate comprehension of spoken language demands the segmentation of continuous speech into discrete words, just as the perception of actions demands the segmentation of perceived activity into discrete events. And listeners must learn to deal with the variability in speech sounds in order to treat some sounds as belonging to the same category, just as they must group, say, disparate dog sounds as belonging to a single "barking" category. One experiment will investigate the extent to which rate information can affect the segmentation of events, while another will assess the extent to which biases that seem to be present in phonetic category learning can also be found in non-speech category learning. A third experiment will use magnetoencephalography (MEG) to probe the acquisition of certain types of speech sound categories. All told, the research will illuminate whether and which processes in language and in other domains parallel each other, which relates to the notion of modularity, the idea that the brain houses separate components that have evolved to perform individual functions in the world.
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