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Your final project for LSCI 1 1 9 / 2 1 9 will be a brief squib ( a short paper ) , which is

Your final project for LSCI 119/219 will be a brief squib (a short paper), which is due June 14th at Data from Kenstowicz & Kisseberth 1979, p.72) Here are the data: /laq/: noq-laq-Wi:y-a 'ears are stopped up'
noq-lg-a 'ears are almost stopped up'
hos-taq-laq 'make him stop!'
hos-taq-lg-a 'makes someone stop an action'
toq-lg-a 'stops an action'
/plaq/: sno-ntap-laq-s 'rotted wokas ?5'
sno-ntap-lg-a 'causes to rot down'
? How about an OT analysis? Can we easily rule out * qulq qlq? anti-nuclear constitution
Data here from Josephs 1990
these are quite broad transcriptions and there's a lot more to it
check out
tekinged.com to hear crowd-sourced recordings of Palauan words
? Account for length and quality alternations (you'll need 2 rules).
11:59 pm. This paper should be at least four pages, and should consist of the following
components:
1. Create or find a dataset that has some interesting property with respect to theory
comparison. Some of the properties weve focused on in class so far are:
a. Opacity (counterfeeding, counterbleeding)
b. Lookahead/sour grapes
c. Myopia (the opposite of lookahead)
d. Multi-site optionality
e. Conspiracies
2. Perform an analysis of this data in at least two of the frameworks listed below.
a. SPE (with simultaneous rule application)
b. SPE (with directional iterative rule application)
c. Optimality Theory
d. Harmonic Serialism
e. Harmonic Grammar (covered in Week 9)
f. Maximum Entropy OT (covered in Week 10)
Your analyses should follow the same format as the assignments: that is, clearly define your
rules/constraints, choose derivations/tableaux that demonstrate necessary
orderings/rankings.
3. Compare the analyses in the two frameworks. For example:
a. Are both frameworks able to capture the patterns in the data (e.g. for an opaque
pattern, can SPE and OT both predict the correct outcomes)?
b. Do you need to make certain assumptions to account for the data under one of the
models (e.g. did you need to use conjoined constraints to make an OT analysis of an
opaque phenomenon work? Some other type of constraint we havent discussed in
class?)
c. If both analyses work, can you think of any reasons to prefer one over the other?
In essence, this is like the homework assignments but youre producing two analyses of a single
data set and comparing them.
Tips on finding data
There are a few options for where you can find an appropriate data set:
Put a new one together based on a language you or someone you know speaks (or based on
reference materials). This is the most work, but likely to be the most interesting! If you are
interested in this and dont have a good idea of how to approach it, message Connor for
help. This is a great option if youre interested in grad school (or you are currently a grad
student).
Find an existing dataset that we havent talked about in class by looking at papers,
textbooks, etc. Ive uploaded Bruce Hayes phonology textbook, which has some examples
of several relevant problem sets if you search for terms like counterfeeding etc.
Use a dataset that we have talked about in class. The key thing here is that you cannot
compare models we have already explicitly compared in class: so e.g., we compared
SPE and OT analyses of the Lena Asturian data set in class, so this would not be appropriate
for your squib.
A few concrete suggestions:
Take (a subset of) the Uyghur data from HW1, analyze it in OT (or some other framework)
and compare against your rule-based analysis. If you didnt do well in HW1, this could be an
opportunity to revise your analysis.
The Palauan data from Lecture 4, p.8(dont worry about accounting for stress position).
The Polish data from Lecture 4, pp.11-12
The Southern Kikuyu data from Lecture 10, pp.6-7(we already compared this in SPE and OT,
but HS could be interesting)
Tianjin tone sandhi from Lecture 10, pp.12-13
Collaboration and citation
As usual, its fine to collaborate so long as you (a) write up your individual paper; and (b) list your
collaborators at the top.
If you rely on existing work for either datasets or details of your analysis, you must cite your
sources. Its fine to use elements of a published analysis in your write-up, but you need to be clear
when youre doing so vs. when youre proposing your own analysis
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