Word frequency effects in sound change as a consequence of - PowerPoint PPT Presentation

Word frequency effects in sound change as a consequence of perceptual asymmetries: An exemplar-based approach Paper by S. Todd, J. B. Pierrehumbert, J. Hay Presenter: Sven Kirchner Seminar: Exemplar Theory, Prof. Dr. Bernd Möbius SS 2020

Contents • Introduction • Model implementation • Model description • Modeling single and two category movement • Conclusion

Contents • Introduction • Model implementation • Model description • Modeling single and two category movement • Conclusion

• People spend more time listening than speaking • Listened speech stored in memory • Importance of listener over speaker • Speaker- based models may overpredict speaker’s avoidance of ambiguity • Use of listener-turned-speaker model • Papers deals with so-called regular sound change

• Regular sound change : Gradual transformation of the phonetic realization of a phoneme over time

• Regular sound change affects phonemes at different rates for different hypotheses: • Neogrammarian hypothesis: Change affects all phonemes at the same rate, principle of strict modularity • Frequency Actuation Hypothesis: Word frequency effects different depending on motivation of change

Frequency Actuation Hypothesis • Philips (1984): physiologically motivated changes and non-physiologically motivated changes • /t/-tapping as physiologically motivated change, reducing articulatory effort -> high frequency words predicted to change faster • deletion of glides after coronal stops as non-physiologically motivated change -> high frequency words predicted to change slower

Three main studies • /t/-tapping in New • /t/-glottaling in • / ɛ/ - raising in New Zealand English Manchester Zealand English English Affects high- frequency words Affects high- slower than low- frequency words Affects all words at frequency words faster than low- the same rate frequency words -> not supported by -> not supported by FHA -> supported by FHA FHA

Contents • Introduction • Model implementation • Model description • Modeling single and two category movement • Conclusion

/t/-glottaling • Model as a directed phonetic drift of a single isolated phoneme • Sound change only affects /t/, unlikely to affect other phonemes -> single phoneme category subject • Expect low and high-frequency words to change at same rate

/t/-tapping • Produced more like an existing phoneme: /d/ • Competition between two phonemes • Expect model to show faster movement for high frequency words

/ ɛ/ -raising • Interaction between phonemes /æ / and /ɛ/ • Model as system containing two phonemes where one is biased towards the other • Expect model to show slower movement for high-frequency words

Model desiderata 1. Generate movement for each category 2. Maintain shape of each category 3. Maintain distance between categories (two category model only) 4. Maintain overlap of two categories (two category model only)

• A) Intrusive Force • B) Spreading Force • C) Repulsive Force • D) Squeezing Force

• Repulsive force pushes overlapping parts away from each other, enforcing aversion of acoustic ambiguity • High frequency words robustly recognized in face of ambiguity, thus less prone to repulsive force

• Model uses exemplars, episodic traces of experienced instances • Basis of comparison for categorizing other instances of spoken words • Misconception of exemplar-based models privileging high-frequency words

Contents • Introduction • Model implementation • Model description • Modeling single and two category movement • Conclusion

• Model as a production-perception loop • Phonemes in question are vowels • Words as monosyllabic • Three different representations: category, type, exemplar • Number of exemplars as type frequency • Arranged in an exemplar space

Categories • Phonemes representing an abstract generalization over experienced instances of that phoneme in words • E.g map, lab, cat for /æ/

Types • Type consisting of phonological frame and category • E.g. word map with phonological frame m_p and category /æ/

Exemplars • Exemplars as detailed memory trace of instances of that type • Slightly different realizations of a category • Simulations include 492 exemplars per category

• Selection of a type weighted by frequency

• Selection of exemplar out of type, independent of previous selections

• Shift target value by a small amount, so-called bias • Represents influences like reduction of articulatory effort -> Intrusive force (bias force) • Parameter β

• Imprecision represents natural variability • Yields spreading force (Imprecision force) • Model parameter l

• Transmission connection between speaker and listener • Creates closed loop in the model

• Activation of specific exemplar with a window • Overall category activation • Window size as parameter α

• Identification of type of token • Not every token identified • Token must pass future evaluation

• Using acoustic value to measure how likely token is identified as a realization of a certain category • Tokens that do not pass discriminability evaluation are rejected and not stored • Evaluation as probabilistic, less likely to be identified in overlap areas • Repulsive force (discriminability force) • δ as parameter, the highly the harder to pass evaluation

• How good is the chosen token in absolute terms • Good representations easily recalled in short and long-term memory • Evaluation as probabilistic, tokens near high activation as more likely to pass • Squeezing force (typicality force) • τ as parameter of model, represents activation threshold

• Storing token only if it passed both evaluations • Overwrites one random exemplar of the same type

Contents • Introduction • Model implementation • Model description • Modeling single and two category movement • Conclusion

Single category movement • Goal of achieving non-distorting category movement • Balancing parameter • Parameter tuning in stepwise process

• Frequency shows no effect on sound change • Bias affects sound change rates, change identical for HF and LF • Explains lack of word frequency effect for /t/-glottaling in Manchester English

Two category movement • Goal of achieving non-distorted category movement • Additionally, keep distance between categories • Balance forces by choosing parameters accordingly

• Model successfully predicts sound change while maintaining shape and distance • Success attributed to discriminability threshold < 1, non-storing of tokens that fail discriminability evaluation, typicality evaluation introduces squeezing force • However: Model generates exact opposite of empirical data (slower rates for HF in Pusher and higher speed for Pushee)

Enhanced model • Literature suggests bias towards high-frequency words in perception • Perception tests showed: ambiguous words were more likely to be identified as words with high-frequency • Idea: Privilege high frequency words in model

• Idea to vary discriminability threshold with word frequency • high-frequency tokens get lower discriminability threshold, thus making it easier for activation

Contents • Introduction • Model implementation • Model description • Modeling single and two category movement • Conclusion

• Model appropriately generates single and two-category movement • Success in model compared to other models due to balancing of forcing from speaker and listener • Listener-based approach as key to fitting to empirical data • Word frequency-based asymmetries in perception can generate effects on sound change • Simultaneously no asymmetries in production