Interpreting sonority-projection experiments: the role of phonotactic modeling Bruce Hayes Department of Linguistics UCLA

Interpreting sonority-projection experiments: the role of phonotactic modeling

Bruce Hayes

Department of Linguistics

UCLA

August 19, 2011 Hayes, Interpreting sonority projection 2

Sonority

No exact phonetic definition, but it plays a major role in phonological patterning.

A typical arrangement of consonants by sonority:

glides >> liquids >> nasals >> obstruents


Sonority sequencing Sonority Sequencing Principle (Sievers 1881;

Jespersen 1904; Hooper 1976; Steriade 1982; Selkirk 1984).

Sonority preferentially rises through syllable-initial clusters, and falls through syllable-final clusters. Large rises (resp. falls) are better.

A pretty good syllable: [pla] A very mediocre syllable: [pta] (tied) A really terrible syllable: [lpa] (reversed)


The sonority projection effect Ask an English speaker: How good a syllable

is [lba]? (horrible sonority violation) How does it compare with [bda]? (merely bad

sonority violation) Idea: [lba] is much worse even though the

English speaker never heard either one during language acquisition.


The effect emerges in controlled experiments Example: Daland et al. (2011) In the following slide: Horizontal axis: sonority difference of

initial cluster, following the theory of Clements (1990)

Vertical axis: ratings by native speakers (victory percentage, all possible pairwise comparisons of the stimuli)


Sonority projection in Daland et al. (2011)


Earlier experimental literature on sonority projection English:

Pertz and Bever (1975) Albright (2007) Daland et al. (2011) Berent, Steriade, Lennertz, and Vaknin (2007) Berent, Smolensky, Lennertz, and Vaknin-Nusbaum

(2009) Korean:

Berent, Lennertz, Jun, Moreno, and Smolensky (2008) Mandarin:

Ren et al. (2010)


Three accounts of sonority projection Universal constraint set (as in Optimality Theory)

Not the whole story: how could such a set be deployed in a grammar that derives sonority projection?

Relative phonetic difficulty in the production of bad-sonority clusters See Redford (2008) and work cited there

Generalized from the data the child hears English has /br/, /pl/, not */rb/, */lp/ — could this be

enough to distinguish /bd/ from /lb/? This is the possibility pursued here.


Research plan Strategy: computational modeling, using Hayes and

Wilson’s (2008) phonotactic learner Goal: develop grammars that model sonority

projection, generalizing from very minimal training data


Earlier work modeling English Daland et al. (2011) use the Hayes/Wilson

learner to project sonority, using English learning data.

But sonority projection has been shown for languages with much smaller onset inventories than English – is projection possible in such cases?


Bwa and Ba Bwa is a fictional language whose branching

onsets are limited to stop + glide. Ba is a fictional language with no branching

onsets at all. Goal: show that sonority projection is

possible, without stipulating the Sonority Sequencing Principle a priori.


Assumptions I: the feature system

From Clements (1990); each feature defines a cutoff on the Sonority Hierarchy.

glides liquids nasals obstruents

[vocoid] + − − −

[approximant] + + − −

[sonorant] + + + −


Assumptions II: a “UG” of constraints, all “sonority regulating” A constraint is sonority-regulating if it looks like

one of these:

For initial clusters, half the sonority-regulating constraints are “sensible”, half “silly” – both included.


Sample list of constraints*[−syllabic][−sonorant]

*[−syllabic][−approximant]

*[−syllabic][−vocoid]

*[−syllabic][−syllabic]

*[+sonorant][−sonorant]

*[+sonorant][−approximant]

*[+sonorant][−vocoid]

*[+approximant][−syllabic]

*[+approximant][−continuant]

*[+approximant][−sonorant]

*[+approximant][−vocoid]

*[−consonantal][−sonorant]

*[−consonantal][−approximant]

*[−consonantal][−vocoid]

*[−consonantal][−syllabic]

*[−syllabic][+sonorant]

*[−syllabic][+approximant]

*[−syllabic][−vocoid]

*[−sonorant][+sonorant]

*[−sonorant][+approximant]


Phonemes of Bwa

p t k ab d gf s v zm n

lr

w j


Features for Bwa Consonants: as given earlier Vowels: no sonority features, only

[+syllabic]


Training data: the full vocabulary of Bwa

pa ta ka ba da ga fa sa va za ma na la ra ja wa

pwa twa kwa bwa dwa gwa

pja tja kja bja dja gja


Weighting the constraints Feed the Hayes/Wilson learner Bwa, with the

a priori constraints just given. Learned a grammar — assigning weights to

the constraints Software used:

http://www.linguistics.ucla.edu/people/hayes/Phonotactics/


Testing the learned grammar Obtain the “penalty

scores” it assigns to 16 syllables that embody every possible sonority sequence

Arrows show well-formedness differences that should be observed if sonority is projected.

wwa wra wma wpa

rwa rra rma rpa

mwa mra mma mpa

pwa pra pma ppa


Result All and only stop +

glide clusters perfect.

They served as the empirical “kernel” for successful sonority projection.


The weights of the learned grammar for Bwa All of the sensible sonority-regulating

constraints got positive weights. All of the silly ones got zero.


Simulation for the Ba Language Training data:

pa ta ka ba da ga fa sa va za ma na la ra ja wa Vowels assumed to have sonority — same

features as glides Same as before:

set of possible constraints training procedure


Results for Ba Again, sonority

projection. This time every

cluster is penalized, but differentially.


Diagnosing the simulations Playing with various constraint sets, I found

that: For projection to happen, the constraints be

sonority-regulating. If you include constraints with all possible

sequences of sonority features, you don’t get projection

Why?


A very simple sonority hierarchy for diagnosis

p m w

[sonorant] − + +

[vocoid] − − +


The sonority-regulating constraintsSensible

*[+vocoid][−sonorant]

*[+vocoid][−vocoid]

*[+vocoid] C

*[+sonorant][−sonorant]

*[+sonorant][−vocoid]

*[+sonorant] C

*C [−sonorant]

*C [−vocoid]

Silly

*[−vocoid][+sonorant]

*[−vocoid][+vocoid]

*[−vocoid] C

*[−sonorant][+sonorant]

*[−sonorant][+voicoid]

*[−sonorant] C

*C [+sonorant]

*C [+vocoid]


The region of possible clusters for Bwa (examples)

*ww *wm *wp

*mw *mm *mp✓pw *pm *pp


What is banned by sensible sonority-regulating constraints? -- “Upward L’”

*[+sonorant] C *C [−vocoid]

(plus 7 more)

*ww *wm *wp

*mw *mm *mp✓pw *pm *pp


All “silly” constraints ban a legal cluster

(total of 9; not all shown)

*ww *wm *wp

*mw *mm *mp

✓pw *pm *pp


What happens when the constraints are weighted? All of the silly constraints forbid [pw] – so they get zero ✓

weight. Two sensible constraints together, *[+sonorant]C and

*C[−vocoid], could do all the work—and maxent does give them the greatest weights.

But the system is cautious—Gaussian prior penalizes big weights on individual constraints

So, descriptive burden is shared among the other sensible constraints.

Basis of sonority projection: the worse the sonority sequencing of the cluster, the more sensible constraints it violates.


What have we got? An explicit grammar that (qualitatively)

matches sonority projection intuitions Learning of the grammars weights from very

minimal information: the sonority drop across /bw/ (in Bwa), across /ba/ in (Ba)


But learning still depends on much a priori knowledge Features that regulate sonority Restriction of sonority constraints to “sonority-

regulating ones” Nothing said yet about codas, where sonority rises

The system must be told to look at the syllable peripheries, so it will generalize properly.

See full version of this paper.


Thank you Full paper is available in conference

proceedings and on line at http://www.linguistics.ucla.edu/people/hayes

Author email: [email protected]

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Interpreting sonority-projection experiments: the role of phonotactic modeling Bruce Hayes Department of Linguistics UCLA