Optimality-Theoretic modelling of phoneme split

1. Optimality-Theoretic modelling of phoneme split Paul Boersma, University of Amsterdam Paola Escudero, McGill University EuroSLA 11, Paderborn September 26, 2001

2. Six hypothesesabout phonemic contrasts • Their production is dialect-dependent. • Their perception is dialect-dependent. • L1 learners achieve optimal perceptiongiven their production environment. • This can be modelled by Optimality Theoryand the Gradual Learning Algorithm. • L2 learners do not necessarily achieveoptimal perception. • This can also be modelled by OT & GLA.

3. We test these six hypotheses on the English /I/-/i/ contrast L1: Scottish Standard EnglishL1: Southern English Standard EnglishL2: Spanish-speaking learners of English

4. Adult native Scottish production

5. Adult native Southern production

6. Six hypothesesabout phonemic contrasts • Their production is dialect-dependent. • Their perception is dialect-dependent. • L1 learners achieve optimal perception. • This can be modelled by OT & GLA. • L2 learners do not necessarily achieveoptimal perception. • This can also be modelled by OT & GLA.

7. Adult native perception Scottish Southern

8. Six hypothesesabout phonemic contrasts • Their production is dialect-dependent. • Their perception is dialect-dependent. • L1 learners achieve optimal perception. • This can be modelled by OT & GLA. • L2 learners do not necessarily achieveoptimal perception. • This can also be modelled by OT & GLA.

9. Why does perception have to depend on the production environment? • Answer: to optimise perception, the listener has tominimise the probability ofperceptual confusion • The optimal perception strategy, therefore, is:likelihood maximisation, i.e.choose the most likely produced category,given a certain F1 & duration

10. Average production environment: Scottish Southern Optimal perception (max. likelihood): 82.5% 87.1%

11. Six hypothesesabout phonemic contrasts • Their production is dialect-dependent. • Their perception is dialect-dependent. • L1 learners achieve optimal perception(they integrate the two acoustic cues). • This can be modelled by OT & GLA. • L2 learners do not necessarily achieveoptimal perception. • This can also be modelled by OT & GLA.

12. Native English constraint set “260 Hz should not be perceived as /I/” “260 Hz should not be perceived as /i/” “500 Hz should not be perceived as /I/” “500 Hz should not be perceived as /i/” “60 ms should not be perceived as /I/” “60 ms should not be perceived as /i/” “180 ms should not be perceived as /I/” “180 ms should not be perceived as /i/” …and so on, for all F1 and duration values

13. Average production environment: Scottish Southern Optimal perception (max. likelihood): 82.5% 87.1%

14. Scottish optimal perception in OT Southern optimal perception in OT

15. How is the knowledge acquired? • Whenever the listener makes a categorization error, she applies a Gradual Learning Algorithm:

16. Simulated Scottish L1 development baby 4 months 1000 months 50.0% 85.3% 87.0% (optimal: 87.1%)

17. Simulated Southern L1 development baby 4 months 1000 months 50.0% 79.7% 82.5% (optimal: 82.5%)

18. Six hypothesesabout phonemic contrasts • Their production is dialect-dependent. • Their perception is dialect-dependent. • L1 learners achieve optimal perception. • This can be modelled by OT & GLA. • L2 learners do not necessarily achieveoptimal perception. • This can also be modelled by OT & GLA.

19. Typical L2 categorization by Spanish learners of English Scotland Southern England

20. Six hypothesesabout phonemic contrasts • Their production is dialect-dependent. • Their perception is dialect-dependent. • L1 learners achieve optimal perception. • This can be modelled by OT & GLA. • L2 learners do not necessarily achieveoptimal perception. • This can also be modelled by OT & GLA.

21. Native Spanish constraint set “260 Hz should not be perceived as /i/” “260 Hz should not be perceived as /e/” “260 Hz should not be perceived as /a/” “260 Hz should not be perceived as /o/” “260 Hz should not be perceived as /u/” low ranked or non-existent: “60 ms should not be perceived as /i/” “60 ms should not be perceived as /e/” “60 ms should not be perceived as /a/” “60 ms should not be perceived as /o/” “60 ms should not be perceived as /u/” …and so on, for all F1 and duration values

22. Constraint set of Spanish learners of English “260 Hz should not be perceived as /i/” “260 Hz should not be perceived as /e/” “260 Hz should not be perceived as /a/” “260 Hz should not be perceived as /o/” “260 Hz should not be perceived as /u/” “60 ms should not be perceived as /short/” “60 ms should not be perceived as /long/” …and so on, for all F1 and duration values, but: no F1-to-/length/ mappings; no duration-to-/vowel quality/ mappings.

23. Strategy of a Spaniard in Scotland Two-category assimilation: English /i/  L2 /i/ English /I/  L2 /e/

24. Simulation of a Spaniard in Scotland 200 months 204 months 1000 months 74.9% 83.5% 87.2% (optimal: 87.1%)

25. Strategy of a Spaniard in S.England New length contrast: English /i/  L2 /i:/ English /I/  L2 /i/

26. Simulation of a Spaniard in S.England 200 months 204 months 1000 months 50.0% 79.0% 79.3% (optimal: 82.5%)

27. Six hypotheses, now finally confirmed by us, about phonemic contrasts • Their production is dialect-dependent. • Their perception is dialect-dependent. • L1 learners achieve optimal perception. • This can be modelled by OT & GLA. • L2 learners do not necessarily achieveoptimal perception. • This can also be modelled by OT & GLA.

28. A possible assimilation pattern Spanish S.English has 2x5 vowels (7 symbols): Native S.English has 12 arbitrary symbols: I— i i—i E— e e—e a—a , —A o—o — o u—u U— u

29. Discussion • GLA generally leads to optimal perception, but it depends on the appropriateness of the constraint set. • L2 learners seem to have constraint sets that are too restricted for the new language environment. • The restricted constraint set does not seem to cause the L2 learner much harm. • Adding a new contrast on the basis of duration seems to be easier than splitting existing vowel quality categories.

30. Thank you for your attention!