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Roles of meaning predictability in language production and learning
Chigusa Kurumada1 & Scott Grimm2 1Department of Brain and Cognitive Sciences, 2Department of Linguistics University of Rochester
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Frequent/predictable words are likely reduced or omitted (e.g., Zipf, 1949; Jurafsky et al., 1996; Alyett & Turk, 2003; Bell et al., 2003)
Predictability and linguistic encoding
Predictability of… what? Form? Meaning?
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This talk: Plural marking morphology
English
pea Basic form pea-s plurative form
pys “peas” Basic form pys-en “pea” singulartive form
Haspelmath & Karjus (2017)
Welsh
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This talk: Plural marking morphology
Dagaare
bíé “child” Basic form bíí-rí “children” plurative form
bíè “seeds” Basic form bì-rí “seed” singulartive form
Grimm (2012)
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Optimizing efficiency?
§ Capitalizing linguistic signal on a meaning that is
otherwise less predictable (= less likely to be inferred)
Plural meaning more predictable
Overt singulartive marking
Plural meaning less predictable
Overt plurative marking
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Current study: Optional Plural Marking in production
Plural meaning more predictable
Less overt plural marking
Plural meaning less predictable
More overt plural marking
§ Capitalizing linguistic signal on a meaning that is otherwise less predictable (= less likely to be inferred)
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How do we estimate the meaning predictability?
Based on Haspelmath & Karjus (2017)
-0.8 -0.4 0 0.4 0.8 1.2
girl boy
apple ear leg
pigeon stawberry
bee glove
ski potato
shoe American
§ Odds of Plural vs. Singular forms (e.g., “shoes” / “shoe”)
.4 .8 -.4 0
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How do we estimate the meaning predictability?
Based on Haspelmath & Karjus (2017)
-0.8 -0.4 0 0.4 0.8 1.2
girl boy
apple ear leg
pigeon stawberry
bee glove
ski potato
shoe American
§ Odds of Plural vs. Singular forms (e.g., “shoes” / “shoe”)
.4 .8 -.4 0
Rose dissertation (2017) w/ Jen Hay
girl-s
Phonetic duration of –s longer for words with lower plural predictability
shoe-s shorter longer
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Question 1
Is predictability of plural meaning a significant predictor of optional plural marker use?
Plural meaning less predictable
Plural meaning more predictable
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Experiment 1: Artificial language learning study (e.g., Fedzechkina et al., 2012)
Learning: 4-alternative-forced choice
Sentence comprehension
Subjects: 40 speakers of American English
Production: Prompted sentence production
Material: 12 novel nouns / 1 novel verb
Optional plural marker “-ka”
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Word presentation: (12 * 2 = 24 trials)
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Word presentation: (12 * 2 = 24 trials)
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Word learning: 4 alternative forced choice (48 trials)
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Word learning: 4 alternative forced choice (48 trials)
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Sentence comprehension (12 items * 4 = 48 trials)
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Sentence comprehension (12 items * 4 = 48 trials)
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Sentence production (12 items * 2 = 24 trials)
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Meaning predictability manipulation
§ They are learning:
§ Words
§ Plural predictability (including fillers in 4AFC trials)
animals
insects 25%
75% 25%
75%
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Meaning predictability manipulation
animals
insects 25%
75% 25%
75%
§ Prediction: Less overt -ka use for [ insects ] when presented as multiples
-ka
-ka
2/3 (66%)
2/3 (66%)
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Results1: Proportions of plural marker use P
ropo
rtion
of –
ka u
se
Animals Insects
.25
0
.5
.75
1.00
singleton multiple multiple singleton
66%
p<.03
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1. Optional plural marking more likely when the plural meaning is less predictable
2. Restructuring of the marking patterns (The animal vs. insect asymmetry not present in the input)
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animals
insects 25%
75% 25%
75%
-ka
-ka
Summary 1: Animals vs. Insects
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Summary 1: Animals vs. Insects
§ Plural meaning predictability higher for insects
§ Where does this knowledge come from?
p(plural | ) > p(plural | )
World knowledge Exposure input
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Question 2
Is predictability of plural meaning learnable based on the input statistics?
Plural meaning less predictable
Plural meaning more predictable
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Experiment 2: Replicating Exp.1 w/ new referents
Learning: 4-alternative-forced choice
Sentence comprehension
Subjects: 40 speakers of American English
Production: Prompted sentence production
Material: 12 novel nouns / 1 novel verb
Optional plural marker “-ka”
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Results 2: Predictability based on the input?
Pro
porti
on o
f –ka
use
1.00
.75
.5
.25
0 singleton singleton multiple multiple
Red shapes Blue shapes
p<.02
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Results 2: Predictability based on the input?
Prop
ortio
n of
–ka
use
sing
leto
n
mul
tiple
sing
leto
n
mul
tiple
mul
tiple
mul
tiple
sing
leto
n
sing
leto
n
n.s.
Predictability of plural meaning is learnable based on the input statistics.
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Conclusion: Form vs. Meaning predictability?
Bias towards explicitly encoding meaning that is otherwise less predictable.
Can we count meaning (independent of frequencies of word/linguistic forms)?
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Thanks to: Masha Fedzechkina (University of Arizona) T. Florian Jaeger (University of Rochester) Experimental Semantics and Pragmatics group
RAs: Wesley Orth (Northwestern University) Joseph Plvan-Franke (University of Rochester) Rachel Myers (University of Rochester)
Thank you!
summary: language learners can learn differential predictabilities of the plural meaning for noun classes and make efficient use of optional plural marking morphology.
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Results 2: Inferability beyond animacy
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1. Linguistic communication as a inference problem over noisy input given world/linguistic/context knowledge
2. Speaker balance between 1) speed / ease / effort and 2) robust (successful) information transfer
3. Provide more linguistic signal for message (parts) otherwise less predictable
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Efficiency-based account: 3 key assumptions
signals inferences