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April 2021
Colloquium with Kristen Syrett (Rutgers)
Zoom link: https://ucla.zoom.us/j/98929850267?pwd=Y3hUdi9RSG5ITG9UT0ZGRUFReU5hdz09 Meeting ID: 989 2985 0267 Passcode: colloquium Abstract: Making comparisons and interpreting comparatives in child language Rutgers University – New Brunswick For many years now, researchers in language and cognitive development have been plagued by children’s divergent non-adult-like productions of comparative constructions, and their apparent inability to properly interpret even the most basic of comparatives (although researchers have also thrown some complicated ones their way!). The source of the difficulty has been alternatively attributed to a lack of understanding…
Read MoreFebruary 2021
Colloquium Talk with Jeremy Steffman
Prosodic context in speech perception When listeners process spoken language, they extract information about (1) segmental categories, defining the words intended by a speaker and (2) prosodic features, which convey information about prominence, grouping, and so on (i.e. how the words are said). These two parts of understanding spoken language are often studied as separate, however, their joint influence in structuring acoustic information in the speech signal suggests that they might interact in perception. This talk presents an exploration of one sort…
Read MoreJanuary 2021
Colloquium Talk with Molly Babel
Molly Babel (UBC). Faculty host: Claire Moore-Cantwell. Zoom link: https://ucla.zoom.us/j/99599993759?pwd=NkQwQnRwNkpqWGRMTGV1dG1FbUxyUT09 Email the Colloquium Committee at uclacolloquium@gmail.com to be added to the listserv. For guest outside of UCLA, please submit an RSVP for colloquiums you would like to attend. Abstract: When do listeners care about phonetic variation? Spoken language is immenselyvariable. Some of that variation may be associated with social categories andsome may be idiosyncratic to an individual’s voice. Either of these sources ofvariation may affect the typical patterning of meaningful contrasts…
Read MoreNovember 2020
Colloquium Talk with Jessica Coon
Jessica Coon (McGill University). Faculty host: Harold Torrence. Zoom link will be available one week before the talk. Email the Colloquium Committee at uclacolloquium@gmail.com to be added to the listserv. For guest outside of UCLA, please submit an RSVP for colloquiums you would like to attend.
Read MoreOctober 2020
Colloquium Talk with Gillian Gallagher
Phonetic variability and natural class phonotacticsGillian Gallagher, NYU Phonological patterns are stated over classes of sounds, usually defined based on a shared phonetic property. Phonetic sound changes and phonetic variation, however, are both extremely common, and easily result in a language showing a phonological pattern over a class of segments that cannot be easily defined given the synchronic phonetic system. In this talk, I look at such a case in South Bolivian Quechua, where the etymological plain uvular stop /q/ has…
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Hannah Sande (Georgetown University). Faculty host: Ethan Poole Zoom link will be available one week ahead of the talk.
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Joe Pater (UMass). Faculty host: Claire Moore-Cantwell Zoom link will be available one week ahead of the talk.
Read MoreDecember 2019
Colloquium: Nathan Klinedinst – Anaphora and Identity
In prominent theories pronouns are treated as having (in effect) descriptive content, to explain the possibility of anaphora on indefinites outside their binding domain. We discuss some data that appears to be problematic for these approaches, and consider as an alternative, a view that treats pronouns as simple variables and tracks anaphoric dependencies separately.
Read MoreNovember 2019
Colloquium: Will Styler – Using Transparent Machine Learning to study Human Speech
Using Transparent Machine Learning to study Human Speech Machine learning, the use of nuanced computer models to analyze and predict data, has a long history in speech recognition and natural language processing, but has largely been limited to more applied, engineering tasks. This talk will describe two more research-focused applications of transparent machine learning algorithms in the study of speech perception and production. For speech perception, we’ll examine the difficult problem of identifying acoustic cues to a complex phonetic…
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