10th February 2023 12:25 PM

Samuel Andersson will give an informal talk on "Iterativity in Phonological Processes"

Abstract:

Some phonological processes have the opportunity to apply more than once within a phonological domain, as in some varieties of Spanish: /islas/ [ihlah] 'islands' with two applications of debuccalization of /s/ to [h]. It is a longstanding issue in phonology whether such processes apply simultaneously (all applications at once) or iteratively (one application at a time).

I discuss preliminary typological data addressing this question, arguing that optionality and within-speaker variation may prove crucial in furthering our understanding of phonological iterativity.

10th February 2023 04:30 PM

Samuel Andersson will have an informal Phonology discussion with our grad students

Samuel Andersson will discuss Phonology with core grad students prior prior to dinner with these students.

15th February 2023 12:10 PM

PhonDAWG - Phonetics Lab Data Analysis Working Group

Simon will discuss an experiment in preparation.

And in light of the recent B11 water intrusion, we will discuss emergency procedures.

16th February 2023 04:30 PM

Linguistics Colloquium Speaker: Jennifer Kuo will discuss "When Phonological Learning is Not Statistical: How Learning Biases have Reshaped Malagasy Paradigms"

The Department of Linguistics proudly presents Jennifer Kuo (she/her), PhD student in the Department of Linguistics, UCLA.  The title of Jennifer's talk is:

"When Phonological Learning is Not Statistical: How Learning Biases have Reshaped Malagasy Paradigms".

ASL interpretation for the talk will be provided.   Her talk will be followed by reception in the Linguistics lounge (Room 208 Morrill Hall).

Abstract:

One view of phonological learning is that it is driven by a domain-general bias towards frequency-matching, and therefore predictable from statistical distributions of the language (Albright 2002; Ernestus & Baayen 2003; Nosofsky 2011). A competing view is that learning is influenced by various linguistically-motivated biases, such as a bias towards less complex patterns.

One way to tease apart these effects is to look at how learners behave when presented with conflicting data patterns––they do not always replicate the language they hear from their parents, and their errors (such as goed instead of went) can be informative, telling us about what biases are present in learning. Such errors can be adopted into speech communities and passed through generations of speakers, resulting in reanalysis of a data pattern.  

In this talk, I look at reanalyses over time in Malagasy and show that reanalysis is not entirely predictable from statistical distributions.

Instead I argue that Malagasy reanalysis is sensitive to both frequency-matching and a markedness bias, using an iterated version of Maximum Entropy Harmonic Grammar (Smolensky 1986; Goldwater & Johnson, 2003) that simulates the cumulative effect of reanalyses across generations of speakers.

I further propose that the markedness effects active in reanalysis are restricted to those already present in the language as a phonotactic tendency, and show that this is the case for Malagasy.

These results demonstrate how findings from language change over time, combined with quantitative modeling, can give us insight into phonological learning.

Bio:

Jennifer is primarily interested in the structure of paradigms, and how different learning biases affect the learning of paradigms. She addresses this question by looking at paradigm reanalysis over time, and how markedness effects and frequency-matching interact to influence the direction of reanalysis. In more recent work, she is supplementing these findings with experimental evidence from Artificial Grammar Learning experiments.

Jennifer’s CV is here: https://www.kuojennifer.com/cv/.