anna mai, eric bakovi , & matt goldrick | department …annamai.net/mai bakovic goldrick 2018...

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FUTURE DIRECTIONS Phonological opacity as local optimization in Gradient Symbolic Computation Anna Mai, Eric Baković, & Matt Goldrick | Department of Linguistics, UC San Diego; Department of Linguistics, Northwestern University INTRODUCTION GSC optimizes two sets of constraints: a set specifying a Harmonic Grammar, and a set of quantization constraints that prefer discrete symbolic structures. Quantization strength q = dynamic increases during optimization so the system terminates in a discrete symbolic state. During optimization: blend states where multiple symbolic candidates are simultaneously present in the representation. i.e., vowel height may be [0.1, 0.9], a blend of 0.1[high] and 0.9[low], at some point of the computation. PROPOSAL COUNTERBLEEDING IN YOKUTS Yowulmne Yokuts (Californian) High long vowels undergo lowering (1a,b) Long vowel shortening in closed syllables (1b, 2b). All other vowels surface faithfully in height and length (e.g., 2a). Both lowering and shortening when only shortening will do (1b). CONSTRAINT INTERACTION? Proper quantization rate: optimization terminates at the grammatical optimum, the symbolic state assigned highest harmony by the Harmonic Grammar. Quantization improperly regulated: the progressively lower harmony of intermediate blend states traps the optimization process near locally optimal, globally suboptimal outputs. We propose that this underlies counterbleeding patterns. SIMPLIFIED MODEL SYSTEM Base case: Optimization initiated to Long High Input; q increased from 0. Two features for height and length, limited to closed syllables. Counterbleeding. When quantization strength increases rapidly, activations are quickly driven towards extreme values. [high], suppressed by initially strong activation of [long], is therefore unable to increase its activation. Bleeding. When quantization increases slowly, [high] is less suppressed during initial phases of optimization (see inset). As activation of [long] decreases, [high] is therefore able to increase its activation. FULL TYPOLOGY INTUITION Advantage of too many solutions: *L ONGHIGH better satisfied by shortening (suppress [long]) or by lowering (suppress [high]). Advantage of blend states: greater combined amounts of [long] and [high] contribute to greater violation of *L ONGHIGH. Suppress both [long] and [high] to better satisfy *L ONGHIGH. [email protected], [email protected], [email protected] Salt Lake City | Jan. 2018 (1) a. /c’uːm+al/ [c’oː.mal] ‘might destroy’ b. /c’uːm+hun/ [c’om.hun] ‘destroys’ (2) a. /doːs+ol/ [doː.sol] ‘might report’ b. /do:s+hin/ [dos.hin] ‘reports’ /c’u:m+hun/ M:*L ONG H IGH M:*L ONG C LOSED F:I D H EIGHT F:I D L ENGTH Remarks c’u:m.hun *! *! faithful c’o:m.hun *! * lowering c’um.hun * shortening c’om.hun *! * opaque Counterbleeding: interaction of two patterns. Does this hold in GSC? 3 feat. system; syll. opening/closing blocked by high-ranked constraint Markedness only: *L ONGHIGH + *L ONGCLOSED w/ varying weights Initial state: harmony maximum when q = 0 (no input) Optimization process: stochastic noise s.d. = 0.1, q at fixed value (1,000 simulations) Interaction of 2 markedness constraints reduces opacity effects Opacity strongest when *L ONGHIGH operates alone Magnified by bad system dynamics (high q) Using 3 feature system, including faithfulness (and initializing to fully faithful candidate), examine typology — the set of patterns yielded by all constraint weighting conditions. q increased from 0 to 200 at rate of 15. No noise in optimization. The typologies of interest include eight patterns yielded by the basic Harmonic Grammar, plus the counterbleeding pattern: 1. fully faithful 2. shorten long high Vs 3. lower long high Vs 4. shorten long Vs in closed syllables 5. shorten long high Vs in closed syllables 6. A) shorten long high Vs; B) shorten long Vs in closed syllables (A, B unordered) 7. A) shorten long high Vs in closed syllables; B) lower long high Vs (A bleeds B) 8. A) shorten long Vs in closed syllables; B) lower long high Vs (A bleeds B) 9. A) shorten long Vs in closed syllables; B) lower long high Vs (A counterbleeds B) The simulated typology also includes five undesired patterns. (‘A = B’ means that A and B must apply simultaneously): 10. lower long high Vs in open syllables 11. A) lower long high Vs; B) shorten long high Vs in closed sylls (A = B) 12. A) shorten long high Vs; B) lower long high Vs in open sylls (A = B) 13. A) shorten long closed; B) shorten long high; C) lower long high open (B = C) 14. A) shorten long closed; B) shorten long high; C) lower long high (A, B = C) CONCLUSIONS Research supported by NSF grant BCS1344269. Many thanks to Pyeong Whan Cho, Paul Smolensky, and audiences at Northwestern University, UC San Diego, and Washington University for helpful comments, and to Karen Liou and Tim Ressler for helpful scripting. An analysis of counterbleeding interactions is within the reach of GSC’s dynamic optimization over blend state representations. The resulting typology is at present insufficiently constrained, but there are promising avenues for future work. Understanding and curtailing the non-interactive opaque behavior of quadratic constraints. Possible approach: increase complexity of constraint functions s.t. activation of different features contributes differentially to violation. e.g., suppression of [high] is more effective than suppression of [long] in order to satisfy *L ONGHIGH combined (opaque) suppression of [high] and [long] would then need to be reinforced via interaction with e.g. *L ONGCLOSED Applying these same methods to other opaque interactions. Counterfeeding Self-destructive feeding Saltation (aka derived environment effects)

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Page 1: Anna Mai, Eric Bakovi , & Matt Goldrick | Department …annamai.net/Mai Bakovic Goldrick 2018 SCiL poster.pdfPrinting: This poster is 48” wide by 36” high. It’s designed to be

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FUTURE DIRECTIONS

Phonological opacity as local optimization in Gradient Symbolic ComputationAnna Mai, Eric Baković, & Matt Goldrick | Department of Linguistics, UC San Diego; Department of Linguistics, Northwestern University

INTRODUCTION

• GSC optimizes two sets of constraints: • a set specifying a Harmonic Grammar, and• a set of quantization constraints that prefer discrete

symbolic structures. • Quantization strength q = dynamic

• increases during optimization so the system terminates in a discrete symbolic state.

• During optimization: blend states where multiple symbolic candidates are simultaneously present in the representation. • i.e., vowel height may be [0.1, 0.9], a blend of 0.1[high] and

0.9[low], at some point of the computation.

PROPOSAL

COUNTERBLEEDING IN YOKUTS

• Yowulmne Yokuts (Californian) • High long vowels undergo lowering (1a,b)• Long vowel shortening in closed syllables (1b, 2b). • All other vowels surface faithfully in height and length (e.g., 2a).• Both lowering and shortening when only shortening will do (1b).

CONSTRAINT INTERACTION?

Proper quantization rate: optimization terminates at the grammatical optimum, the symbolic state assigned highest harmony by the Harmonic Grammar.Quantization improperly regulated: the progressively lower harmony of intermediate blend states traps the optimization process near locally optimal, globally suboptimal outputs.→We propose that this underlies counterbleeding patterns.

SIMPLIFIED MODEL SYSTEM

• Base case: Optimization initiated to Long High Input; q increased from 0. • Two features for height and length, limited to closed syllables.• Counterbleeding. When quantization strength increases rapidly, activations

are quickly driven towards extreme values. [high], suppressed by initially strong activation of [long], is therefore unable to increase its activation.

• Bleeding. When quantization increases slowly, [high] is less suppressed during initial phases of optimization (see inset). As activation of [long] decreases, [high] is therefore able to increase its activation.

FULL TYPOLOGY

INTUITION

Advantage of too many solutions: *LONGHIGH better satisfied by shortening (suppress [long]) or by lowering (suppress [high]).Advantage of blend states: greater combined amounts of [long] and [high] contribute to greater violation of *LONGHIGH.→Suppress both [long] and [high] to better satisfy *LONGHIGH.

[email protected], [email protected], [email protected] SaltLakeCity|Jan.2018

(1) a. /c’uːm+al/ ⟶ [c’oː.mal]‘might destroy’

b. /c’uːm+hun/ ⟶ [c’om.hun]‘destroys’

(2) a. /doːs+ol/ ⟶ [doː.sol]‘might report’

b. /do:s+hin/ ⟶ [dos.hin]‘reports’

/c’u:m+hun/ M:*LONGHIGH M:*LONGCLOSED F:IDHEIGHT F:IDLENGTH Remarks

c’u:m.hun * ! * ! faithful

c’o:m.hun * ! * lowering

☞ c’um.hun * shortening

! c’om.hun * ! * opaque

• Counterbleeding: interaction of two patterns. Does this hold in GSC?• 3 feat. system; syll. opening/closing blocked by high-ranked constraint• Markedness only: *LONGHIGH + *LONGCLOSED w/ varying weights• Initial state: harmony maximum when q = 0 (≈ no input)• Optimization process: stochastic noise s.d. = 0.1, q at fixed value (1,000

simulations)

• Interaction of 2 markedness constraints reduces opacity effects• Opacity strongest when *LONGHIGH operates alone• Magnified by bad system dynamics (high q)

• Using 3 feature system, including faithfulness (and initializing to fully faithful candidate), examine typology — the set of patterns yielded by all constraint weighting conditions.• q increased from 0 to 200 at rate of 15. No noise in optimization.

• The typologies of interest include eight patterns yielded by the basic Harmonic Grammar, plus the counterbleeding pattern:

1. fully faithful2. shorten long high Vs3. lower long high Vs4. shorten long Vs in closed syllables5. shorten long high Vs in closed syllables6. A) shorten long high Vs; B) shorten long Vs in closed syllables (A, B unordered)7. A) shorten long high Vs in closed syllables; B) lower long high Vs (A bleeds B)8. A) shorten long Vs in closed syllables; B) lower long high Vs (A bleeds B)9. A) shorten long Vs in closed syllables; B) lower long high Vs (A counterbleeds B)

• The simulated typology also includes five undesired patterns. • (‘A = B’ means that A and B must apply simultaneously):10. lower long high Vs in open syllables11. A) lower long high Vs; B) shorten long high Vs in closed sylls (A = B)12. A) shorten long high Vs; B) lower long high Vs in open sylls (A = B)13. A) shorten long closed; B) shorten long high; C) lower long high open (B = C)14. A) shorten long closed; B) shorten long high; C) lower long high (A, B = C)

CONCLUSIONS

Research supported by NSF grant BCS1344269. Many thanks to Pyeong Whan Cho, Paul Smolensky, and audiences at Northwestern University, UC San Diego, and Washington University for helpful comments, and to Karen Liou and Tim Ressler for helpful scripting.

• An analysis of counterbleeding interactions is within the reach of GSC’s dynamic optimization over blend state representations.

• The resulting typology is at present insufficiently constrained, but there are promising avenues for future work.

• Understanding and curtailing the non-interactive opaque behavior of quadratic constraints.• Possible approach: increase complexity of constraint functions s.t.

activation of different features contributes differentially to violation.• e.g., suppression of [high] is more effective than suppression of

[long] in order to satisfy *LONGHIGH

• combined (opaque) suppression of [high] and [long] would then need to be reinforced via interaction with e.g. *LONGCLOSED

• Applying these same methods to other opaque interactions.• Counterfeeding• Self-destructive feeding• Saltation (aka derived environment effects)