Mergers in Produc.on and Percep.on. Ka.e Drager (University of Hawai i at Mānoa) Jennifer Hay (University of Canterbury)

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1 Mergers in Produc.on and Percep.on Ka.e Drager (University of Hawai i at Mānoa) Jennifer Hay (University of Canterbury)

2 Big huge thank you to: Our collaborators: Paul Warren, Bryn Thomas, and Rebecca Clifford

3 Mergers- in- progress Produc.on vs. Iden.fica.on vs. Discrimina.on a glimpse into how sounds are stored and accessed in the mind Social informa.on its role in produc.on and percep.on priming with the concept of social informa.on (e.g., concept of a region) Word- based varia.on lexical diffusion real vs. nonsense words Phonological context condi.onally merged

4 The NEAR- SQUARE merger in NZE Merger on [iəә] Most evidence suggests that this is a female- led merger Led by members of lower socioeconomic groups The merger is s.ll in progress: older NZers are more likely to maintain the dis.nc.on than younger NZers

5 NEAR/SQUARE Experiments Hay et al. (2010) Iden.fica.on: played dis.nct tokens one at a.me - par.cipants iden.fied which word they heard in a binary, forced- choice task US & NZ experimenter Produc.on: read words in minimal pairs US & NZ experimenter Odd One Out task: beer bear bare auditory instruc.ons (UK & NZ) wri_en task (US & NZ)

6 Summary of results In produc.on, par.cipants who met with the US experimenter were more likely to maintain a dis.nc.on than those who met with the NZ experimenter (Hay et al. 2009). In iden.fica.on, experimenter iden.ty ma_ers (Hay et al. 2006) merged par.cipants make more errors if they met with the US experimenter but par.cipants who met with the US experimenter were more likely to report that the word pairs were dis.nct. Exposure to instruc.ons/pre- task (Hay et al. 2010) dis.nct par.cipants were more accurate when exposed to UK instruc.ons/us task merged par.cipants were more accurate when exposed to NZ instruc.ons/nz task

7 Our interpreta.on Levels of representa.on that we assume: phone.cally- detailed words/u_erances phonological abstrac.on lexical abstrac.on All levels are indexed to every other level. The phone.cally- rich level is indexed to social informa.on. The other levels are indexed to social informa.on when the rela.onship is above the level of consciousness. Different tasks cause individuals to ac.vate different levels of representa.on

8 iəә biəә bɪɹ biəә biəә biəә beəә biəә beer US beəә bɪəә biəә bɛɹ bɛɹ beəә bare Sketch of exemplar model with word- level distribu.ons of remembered exemplars, and labeling for phonemic category and dialect area, for someone who is merged on NEAR. (Hay et al 2010: 465)

9 Resonance (see Johnson 2006: 495) Merged Dis*nct Phoneme level One distribu.on. Two distribu.ons. Phone.cally- detailed word level Dis.nct speech/concept introduces noise makes distribu.ons overlap even more Two distribu.ons. (adapted from Hay et al. 2010: 467) Dis.nct speech/concept makes more dis.nct. Dis.nct speech/concept increases dis.nc.on between distribu.ons Two distribu.ons. Dis.nct speech/concept makes more dis.nct.

10 Tes.ng our interpreta.on: real vs. nonsense words In exemplar theory, real words would have representa.ons that are phone.cally detailed, while nonsense words would not because they have not previously been encountered. This means that individuals rely on word- based exemplars for real words but must rely on phoneme- based representa.ons for nonsense words.

11 For condi.onal mergers, this means that: In produc.on subjects will be more merged when producing real words because they are relying on phone.cally- detailed word- based representa.ons subjects will be less merged when producing nonsense words because they are relying on phoneme- based representa.ons and the merger is only in some phonological contexts In percep.on provided that there are some people in the community who maintain a dis.nc.on in all contexts, subjects should be more accurate when iden.fying real words because they have stored representa.ons of them

12 The Ellen/Allan merger in NZE Prelateral merger of DRESS and TRAP shell/shall celery/salary melody/malady Condi.oned merger, nearly complete. Vowels are merged near the non- prelateral TRAP token

13 16 Par.cipants: Ellen/Allan Experiment (Thomas 2004; Thomas & Hay 2005) 1) real word produc.on 2) nonce word produc.on 3) real word percep.on 4) nonce word percep.on

14 Results In produc.on, many speakers maintained more separa.on between the vowels when producing nonsense words

15 MALE 7: REAL WORDS F HEAD DRESS TRAP HAD 600 F

16 MALE 7: NONSENSE WORDS F HEAD DRESS TRAP HAD 600 F

17 FEMALE 8: REAL WORDS F DRESS TRAP HEAD HAD F

18 FEMALE 8: NONSENSE WORDS F DRESS TRAP HEAD HAD F

19 This interacts with social class higher SEC lower SEC

20 In Percep.on Some listeners were more accurate at iden.fying vowels in real words than nonsense words.

21 Summary of results Some NZers were more accurate with real words than nonsense words in percep.on But they maintained a greater dis.nc.on with nonsense words than real words in produc.on.

22 Interpreta.on In produc.on, speakers must rely on phoneme- level produc.ons for nonsense words. Phonemic representa.ons also contain the non- prelateral (non- merged) tokens, which pulls the distribu.ons apart. In percep.on, the real word exemplars include *some* dis.nct tokens, which help in iden.fica.on (even though the listeners feel they are guessing)

23 Cot/Caught Experiment (Drager et al. in progress) Same experiment design but with the cot- caught merger hock pod dodd hawk pawed dawd Par.cipants from Hawai i and western states in the con.nental US regions where we would expect the merger in at least some phonological contexts (Labov et al.)

24 All par.cipants were merged to at least some degree, especially before /n/. Par.cipants merged to varying degrees in other phonological contexts: some merged en.rely on LOT whereas others produced the correct vowel in over 65% of tokens.

25 Example of a nearly merged par.cipant pod pawed

26 Example of a nearly merged par.cipant vod vawd

27 Summary of results (so far) Those who maintain some dis.nc.on were more accurate at iden.fying real words than nonsense words in percep.on (p<0.05). In produc.on, these par.cipants were more likely to maintain a dis.nc.on in nonsense words than in real words (p<0.01). Those who were fully merged were more accurate at iden.fying nonsense words than real words in percep.on (p<0.05). They did not produce a dis.nc.on in real or nonsense words (though this is based on auditory analysis acous.c analysis is in progress).

28 Summary of produc.on and percep.on sound task effect for fully merged effect for condi*onal/nearly merged Ellen/Allan Iden.fica.on n/a slightly less accurate with nonse words Produc.on n/a greater dis.nc.on with nonse words cot/caught Iden.fica.on more accurate with nonse less accurate with nonse words words Produc.on merged in both greater dis.nc.on with nonse words

29 In produc.on Speakers produce the merger because they are accessing phone.cally- rich representa.ons of the words. Except when they are producing novel words (i.e., when they don t have phone.cally- rich lexical/u_erance- level representa.ons to rely on). Then, speakers with some degree of dis.nc.on in some real words/phonological contexts are biased by those dis.nct distribu.ons and are more likely to produce a dis.nc.on.

30 In an iden.fica.on task Individuals access phone.cally- rich lexical informa.on, enabling their high accuracy rates despite their feeling that they are guessing. Feel like the words are the same because they are linked to the same phonemic label, but The word- level distribu.ons are not completely overlapping in their representa.ons, so they perform above chance during iden.fica.on. Par.cipants who are fully merged may be more accurate with nonsense words because: they have adopted a spelling- based strategy; par.cipants tune in to some meaningless- to- them phone.c difference and assign a spelling to it, or there may be a greater phone.c dis.nc.on in the cot- caught nonsense s.muli than the real words more analysis and more data are required

31 In sum There are different levels of mental representa.ons. Different tasks (e.g., real vs. nonsense words, produc.on and percep.on tasks) focus on different levels of representa.on. Mergers- in- progress are the ideal medium in which to explore these ques.ons precisely because their mental representa.ons differ across the different levels.

32 References Drager, Ka.e, Jen Hay, & Rebecca Clifford (in progress author order?) The percep.on and produc.on of caught and cot: evidence from real and nonsense words. Hay, Jennifer, Ka.e Drager and Paul Warren (2009) Careful who you talk to: An effect of experimenter iden.ty on the produc.on of the NEAR/SQUARE merger in New Zealand English. Australian Journal of Linguis6cs 29(2): Hay, Jennifer, Ka.e Drager, and Paul Warren (2010) Short- term exposure to one dialect affects processing of another. Language and Speech 53(4): Hay, Jennifer, Paul Warren and Ka.e Drager (2006) Factors influencing speech percep.on in the context of a merger- in- progress. Journal of Phone6cs 34, 4: Thomas, Brynmor (2004) In support of an exemplar- based approach to speech percep.on and produc.on: A case study on the merging of pre- lateral DRESS and TRAP in New Zealand English. Unpublished MA thesis. University of Canterbury, Christchurch, New Zealand. Thomas, Brynmor and Hay, Jennifer (2005) A pleasant malady: The Ellen/Allan merger in New Zealand English. Te Reo 48:

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