Bridging the gap between L2 speech perception research and phonological theory Paola Escudero & Paul Boersma (March 2002) Presented by Paola Escudero March 1, 2002 Optimality Theory and Phonological Theory Seminay Utrecht Institute of Linguistics OTS

Introduction  Linguistics and L2 speech perception Bridging the gap OT and L2: mainly production L2 OT and perception  Aims  Assumptions  Research hypothesis

Aims 1. Incorporate speech perception and phonological theory in an OT model of phonemic categorization 2. Account for a more challenging case of L2 categorization, based on the integration of multiple acoustic cues 3. Account for L2-specific patterns 4. Further test the model with computer simulations that use the initial state and the algorithm that comes with the theory

Assumptions 1. OT can handle the knowledge behind L1 and L2 categorization and their development 2. Full Transfer for the L2 initial state: L1 constraints and L1 rankings 3. Perception modes: L1 and L2 are handle by two separate systems 4. Full Access for L2 learning: access to the Gradual Learning Algorithm and the same strategies use in L1 (e.g. category formation, category split, etc)

Hypothesis  Stochastic OT together with the GLA constitutes a successful model of L1 and L2 phonological development  This model can account for the following observations: 1)Listeners optimise their perception in accord with the productions they encounter 2)First-language (L1) listeners arrive at an optimal perception 3)Second-language (L2) listeners manifest L2- specific optimisation strategies

Overview of the paper 1. Observation 1: perception/production dependency and L1perceptual optimisation Production & perception: differences in the same direction The optimal listener vs. real listeners 2. Hypothesis testing for L1: OT modelling 2.1 The knowledge behind L1 optimal categorization The development of L1 optimal categorization in simulations 2.4 The simulated listeners vs real listeners 3. Observation 2: L2 vowel categorization L2 perception/production dependency & L2 optimization 4. Hypothesis testing for L2: OT modelling L2 initial state, development, simulations, and comparison with real L2 listeners 5. Discussion

Our case 1. The vowels in the contrast have two main acoustic/auditory differences:  F1  Duration 2. We examine the preference patterns of these cues (in production and perception) in two English varieties: Scottish and Southern British English 3. These varieties are the target languages for the Spanish learners of English that will be presented in later sections

Production and perception differences in the same direction

Optimal listener  To optimise perception, the listener has to minimise the probability of perceptual confusion  The optimal perception strategy, therefore, is: likelihood maximisation, i.e. choose the most likely produced category, given a certain F1 & duration

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

L1 Modelling  Constraint set  Modelling the knowledge behind optimal perception  Modelling the development of optimal perception

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

Scottish optimal perception in OT [74 ms, 349 Hz ] 349 Hz not / I / 74 ms not / i / 74 ms not / I / 349 Hz not / i / /I/ /I/ *!* /i//i/ ** [74 ms, 349 Hz ] 349 Hz not / i / 74 ms not / i / 74 ms not / I / 349 Hz not / I / /I//I/ ** /i/ /i/ *!* Southern optimal perception in OT

How is the knowledge acquired?  Whenever the listener makes a categorization error, she applies a Gradual Learning Algorithm: [74 ms, 349 Hz] 349 Hz not / i / 74 ms not / i / 74 ms not / I / 349 Hz not / I / /I//I/ ** ** /i//i/ *!  **

L1 simulations  Initial state  Fed with the production distributions  F1 and duration: 21 steps, 84 constraints ( categories)  1000 data per virtual month  Initial state scores: 50 % correct

Comparisons and preliminary conclusion  Optimal vs. real listeners  Optimal vs. simulated listeners  Simulated vs real listeners  L1 modelling conclusion

L2 production/perception dependency  7 beginners  The more advanced: bimodal distribution Scottish L1 Southern L1 Spanish L2 D E D M D&S S&D S M S E

L2 Optimisation  Also to minimize probability of confusion  Full Access and grammar copying: Initial state = L1 categories and system  Not good enough, thus further optimisation  Full Access to the GLA and to language universal strategies: category boundary, formation, split  L1 and L2 two separate grammars

Native S.English has 13 arbitrary symbols: A possible assimilation pattern Spanish S.English has 2x5 vowels (7 symbols): I — i i — ii — i ,  — A,  E — e  — , o U — u e — ee — e a — aa — a o — oo — o u — uu — u

L2 Modelling  L2 speech perception generalization and our model  Full Transfer: copy of constraints, rankings  Native Spanish constraints  Initial grammars: constraint set & rankings  Further development: boundary shift and length contrast  L2 simulations  Comparison with optimal and real L2 listeners

Discussion  Category reuse and the initial state  One or two perception systems?  Fossilisation  OT modelling  The Algorithm

Conclusion “Our formal model for L2 phonemic categorization successfully accounts for the attested optimal categorization in L1 acquisition as well as for the attested sub- optimal patterns in L2 acquisition,thereby providing the linguistic mechanism that underlies the generalizations forwarded by several previous models of L2 speech perception”