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![Page 1: This material is based upon work supported by NIH under Grant No. F32MH68204-01A1.](https://reader035.fdocuments.in/reader035/viewer/2022062422/56813298550346895d992fa2/html5/thumbnails/1.jpg)
This material is based upon work supported by NIH under Grant No. F32MH68204-01A1.
The effect of experience on the perception and representation of dialects
Meghan SumnerStony Brook University
University of California, Berkeley
![Page 2: This material is based upon work supported by NIH under Grant No. F32MH68204-01A1.](https://reader035.fdocuments.in/reader035/viewer/2022062422/56813298550346895d992fa2/html5/thumbnails/2.jpg)
The basic questions
1. How do listeners accommodate the variation found in the speech signal?
2. What representations are used to perceive and understand speech?
3. What is the effect of experience on perception and representation?
![Page 3: This material is based upon work supported by NIH under Grant No. F32MH68204-01A1.](https://reader035.fdocuments.in/reader035/viewer/2022062422/56813298550346895d992fa2/html5/thumbnails/3.jpg)
The basic questions
1. How do listeners accommodate the variation found in the speech signal?
– Is a surface pattern generalization made across dialectal variants?– Are all variants equally able to map to meaning?
2. What representations are used to perceive and understand speech?
3. What is the effect of experience on perception and representation?
![Page 4: This material is based upon work supported by NIH under Grant No. F32MH68204-01A1.](https://reader035.fdocuments.in/reader035/viewer/2022062422/56813298550346895d992fa2/html5/thumbnails/4.jpg)
The basic questions
1. How do listeners accommodate the variation found in the speech signal?
2. What representations are used to perceive and understand speech?
3. What is the effect of experience on perception and representation?
![Page 5: This material is based upon work supported by NIH under Grant No. F32MH68204-01A1.](https://reader035.fdocuments.in/reader035/viewer/2022062422/56813298550346895d992fa2/html5/thumbnails/5.jpg)
The basic questions
1. How do listeners accommodate the variation found in the speech signal?
2. What representations are used to perceive and understand speech?
– In the long-term, are variants mapped to a single abstract representation, or to individual, exemplar representations?
3. What is the effect of experience on perception and representation?
![Page 6: This material is based upon work supported by NIH under Grant No. F32MH68204-01A1.](https://reader035.fdocuments.in/reader035/viewer/2022062422/56813298550346895d992fa2/html5/thumbnails/6.jpg)
The basic questions
1. How do listeners accommodate the variation found in the speech signal?
2. What representations are used to perceive and understand speech?
3. What is the effect of experience on perception and representation?
![Page 7: This material is based upon work supported by NIH under Grant No. F32MH68204-01A1.](https://reader035.fdocuments.in/reader035/viewer/2022062422/56813298550346895d992fa2/html5/thumbnails/7.jpg)
The basic questions
1. How do listeners accommodate the variation found in the speech signal?
2. What representations are used to perceive and understand speech?
3. What is the effect of experience on perception and representation?
– Does experience with a particular dialect affect perception and representation?
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How can dialects help?
• Consider slender
– Variation:• Compare cross-dialectal variants in immediate and long-term tasks
– slend-er vs. slend-[]
– Experience:• Control participant experience with a particular dialect
– Compare r-full forms of General American (GA) with r-less forms of New York City dialect (NYC) using psycholinguistic tasks
• GA = participants who do not r-drop or exhibit other regionally-marked characteristics
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What can priming tasks tell us?
Form priming: Do listeners generalize a pattern for cross-dialectal variants independent of dialect?
» How well does slend-er prime an identical item slend-er or a cross-dialect item slend-[]?
Semantic priming: Are cross-dialectal variants mapped onto by meaning by listeners independent of dialect?
» Is slend-[] as effective in activating ‘thin’ as slend-er?
Long-term repetition priming: Are cross-dialectal variants mapped onto a single abstract representation, or stored as individual concrete, or exemplar, representations?
» Does slend-er exhibit the same level of identity priming after 20 minutes as slend-[]?
Imm
edia
tepr
oces
sing
Long
-term
repr
esen
tatio
n
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The effect of experience: Participants
• Post-experiment interview & questionnaire
– Interview: Productive r-dropping, yes or no?– Questionnaire:
• Born in what city, state, country (participants, parents, grandparents)• Languages spoken (participants, parents, grandparents)• Other locations lived (including dates)
• 3 listener populations
• Needed 144 participants, ran 207– Some exclusion criteria
• Lived outside NYC area, bilingual, not 1st semester SB students
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• GA– Never lived in the NYC/Tri-State area, or any other r-dropping region– First-semester Stony Brook students (run in 1st month on campus)
• NYC R-less– Lifelong NYC-area residents– Prominent r-dropping
• NYC R-full– Lifelong NYC-area residents– No r-dropping
What’s the difference?
96% of R-less listeners’ parents and grandparents are NYC
natives
* * * * * *
3% of R-full listeners’ parents and/or grandparents are NYC
natives
Three populations
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Familiar voices facilitate processing
Stimuli created with FOUR speakers
Primes produced by two females (one GA, one NYC)
Targets produced by two males (one GA, one NYC)
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Experiment 1: Form priming
Do listeners generalize a pattern for cross dialectal variants independent of dialect?
Typical trial:Auditory prime-target pairs separated by a short interval
Lexical decision made for targets
Prime ISI Target Response(GA Voice 1) (GA Voice 2)
runn-er runn-er “Word”100ms
[ggi] [ggi] “Pseudoword”
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Experiment 1: Form priming design
• Four conditions
Condition Related Prime Target Control Prime
GA – GA runn-er runn-er bak-erNYC – GA run[] runn-er bak-[]GA – NYC runn-er run[] bak-erNYC – NYC run[] run[] bak-[]
• 48 participants (16 for each population)• 160 –er final words• No item or variant presented in more than 1 trial• Counterbalanced lists• Fillers avoid response bias
GA Identity
NYC Identity
1.2.3.4.
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Experiment 1: Form priming predictions
If pattern between variants is internalizedPriming in all conditions, strongest in identity conditions
If pattern between variants is internalizedPriming in all conditions, strongest in identity conditions
If pattern not internalized (arbitrary or new)Benefit for within-dialect variants
If pattern between variants is internalizedPriming in all conditions, strongest in identity conditions
If pattern not internalized (arbitrary or new)Benefit for within-dialect variants
If experience with a variation is criticalDifferences among three listener groupse.g., Difference between NYC R-Less and GA in facilitation of NYC targets
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Form priming effects across dialects
Overt-NYC Covert-NYC GA
Prim
ing
effe
ct (m
sec)
(RT
to R
elat
ed T
arge
t - R
T to
Unr
elat
ed T
arge
t)
-20
0
20
40
60
80
Experiment 1: Form priming results
Condition Prime – Target
GA – GA runn-er – runn-er
NYC – GA run[] – runn-er
GA – NYC runn-er – run[]
NYC – NYC run[] – run[]
Short-term mapping between all variants for NYC participants
No mapping to NYC variants for GA
Lack of experience has clear processing cost
NYC R-Less• Strong identity priming in both dialects
• Reduced variant priming
NYC R-Full• Similar to R-Less participants
• Exposure facilitates processingGA
• Priming only for GA targets• Surface variation not internalized
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Experiment 2: Semantic Priming
Do all variants facilitate the recognition of a semantically-related target?
Typical trial:Auditory prime-target pairs separated by a short interval
Lexical decision made for targets
Prime ISI Target Response(GA Voice 1) (GA Voice 2)
slend-er thin “Word”100ms
[bo] guggy “Pseudoword”
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Experiment 2: Semantic priming design
• Four conditions
Condition Related Prime Target Control
1. GA – GA slend-er (GA voice 1) thin (GA voice 2) filt-er
2. NYC – GA slend[] thin filt[] 3. GA – NYC slend-er thin filt-er
4. NYC – NYC slend[] (NYC voice 1) thin (NYC voice 2) filt[]
• 48 participants (16 for each population)• 160 –er final words and semantically-related targets• Targets chosen via large-scale mass testing experiment• No item or variant presented in more than 1 trial• Fillers included to avoid response biases
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Experiment 2: Semantic priming predictions
• Native dialect primes should facilitate recognition of related targets
• Non-dialect primes should not yield facilitation
If lack of exposure prohibits lexical activation for variants:• Only GA primes should facilitate lexical activation for GA listeners (Cost)
• All variant primes should facilitate lexical activation for NYC listeners (Benefit)
If non-dialect variants do not activate semantically-related items:
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Efficiency of lexical activation for dialect variants across listeners
Overt-NYC Covert-NYC GA
Prim
ing
Effe
ct (m
sec)
(RT
to R
elat
ed T
arge
t - R
T to
Con
trol
Tar
get)
0
20
40
60
80
100
Experiment 2: Semantic priming results
Exposure to two dialects results in equivalent lexical activation across dialects
NYC variant inconsistent with representation resulting in processing cost
Condition Prime Target
GA -GA slend-er thin
NYC -GA slend[] thin
GA -NYC slend-er thin
NYC -NYC slend[] thin
NYC R-Less• All variants equally effective in lexical activation
• Benefit for GA prime
NYC R-Full• Pattern similar to R-Less participants
• Strong semantic priming independent of variant dialect
GA• Priming only for GA primes
• NYC primes are unable to activate lexicon
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How do listeners process cross-dialect variants?
Listeners exposed to both dialects …
– generalize surface pattern • form processing• lexical activation
in the short-term
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The issue of representation
• Striking similarity between R-Less and R-Full in the short term
• Listeners able to generalize surface pattern with experience
• Tasks do not inform us about nature of representations– Issue of representation on backburner– Surface generalizations derived from abstract representations– Evidence that representations (and information they carry) have a
role in speech perception
Question: What do listeners actually represent?
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Experiment 3: Long-term repetition priming
Do listeners store a single abstract representation,
or multiple, concrete representations?
Typical trial:
Individual words presented Lexical decision made for each word
Primes and targets presented in different blocks or listsEffect based on long-term activation of phonological representations
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Condition Block 1: Primes Block 2: Targets
1. GA GA repeated — slend-er
control filt-er filt-er
2. NYC GA repeated — slend-er
control filt-[] filt-er
3. GA NYC repeated — slend-[] control filt-er filt-[]
4. NYC NYC repeated — slend-[]
control filt-[] filt-[]
Condition Block 1: Primes Block 2: Targets
1. GA GA repeated slend-er slend-er
control — filt-er
2. NYC GA repeated slend-[] slend-er
control — filt-er
3. GA NYC repeated slend-er slend-[] control — filt-[]
4. NYC NYC repeated slend-[] slend-[]
control — filt-[]
Experiment 3: Long-term repetition priming design
• 48 participants, 16 of each listener group
• 160 –er final words
• No variant present in more than 1 trial
• Fillers used to eliminate response biases
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Experiment 3: Long-term repetition priming predictions
Expect GA participants to store one representation
Strong within-dialect identity priming
If listeners store multiple, concrete representations:
Strong within- and cross-dialect identity priming
If experience affects representation
Differences among three listener groups (expected)
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Long-term encoding of dialect variants across listeners
Overt-NYC Covert-NYC GA
Prim
ing
Effe
ct (m
sec)
(RT
to R
epea
ted
Targ
et -
RT
to C
ontr
ol T
arge
t)
-20
0
20
40
60
80
Long-term priming: Results
Type of experience plays role
Language use representation
NYC R-Less• Strong identity priming in both dialects
•Two variants stored
NYC R-Full• Similar to GA – single abstract representation
• Representations differ from Overt-NYC
GA• Priming only for GA-GA condition
• Single representationCondition Prime – Target
GA – GA slend-er – slend-er
NYC – GA slend[] – slend-er
GA – NYC slend-er – slend[]
NYC – NYC slend[] – slend[]
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Two critical distinctions can be made:
1. Production and representation
2. Process and representation
Language use is not equivalent to representation
NYC R-Less Participants
• Produced one form in interview but store two representations• Representations not necessarily equivalent
NYC R-Full and GA Participants
• Same representation, different immediate ability to generalize variant pattern
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To sum up …
• Language use is not a predictor of representation
• Evident cost of lack of experience with surface variation
• Experience influences – Immediate processing and representations
• Benefit for canonical form
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Thank You!
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Do these patterns generalize to within-dialect phonetic variation?
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Long-term repetition priming of phonetic variants
flu[t]
flu[t]
flu[]
flare
---
flu[t]
flu[t]
flu[]
flare
flare
Basic
Unreleased
Glottal
Repeated Control
New Control
Most frequent
Are multiple phonetic variants stored as independent forms?
Primes Targets
If multiple, concrete representations are stored …we should find identity priming for all variants
Basic Identity
Unreleased Identity
Glottal Identity
Repeated Identity
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Are multiple phonetic variants stored as independent forms?
Identity Priming for all Variants
Prim
ing
Effe
ct (m
sec)
(RT
to R
elat
ed T
arge
t - R
T to
Con
trol
Tar
get)
0
20
40
60
80
Basic Unreleased Glottal ControlIdentity Identity Identity Identity
• Only Basic [t] identity as strong as repeated control
• Low frequency form encoded most efficiently
• Identity priming indicative of concrete representations
Prime Target
Basic identity flu[t] flu[t]
Unreleased identity flu[t] flu[t]
Glottal identity flu[] flu[]
Control identity flare flare
Benefit for canonical form, even when it is not the
most frequent
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Implications and new directions
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Implications and important questions
1. Benefit for canonical form– Is something about [t] simply more memorable?
• Are certain acoustic cues more salient?– Are abstract generalizations made over sounds or words?
2. Specificity of representations?– Rethink role and nature of representations– At what level do multiple representations exist?
3. What and where do listeners learn?– Specific acoustic cues or robust generalizations?– Is learning pre-lexical or lexical?
Learning and generalization of non-native acoustic cues
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Voicing contrast in native and non-native English
• Native English voicing contrast made with vowel-consonant duration ratio
– Consider beat and bead
• In Polish, final devoicing leads to near neutralization– Contrast made in voicing into closure duration
• Pilot studies1. Native Polish speaker of English transfer this cue to English2. Native English listeners perceive beat and bead as beat
“Bad Map”
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Learning and generalization of non-native cues
How do listeners learn to move from reliance on a native acoustic cue to the use of a new non-native cue?
• Where does learning occur?– Is a cue learned and remapped at the pre-lexical or lexical level?
• What is generalized?– Once a cue is learned, does it generalize to:
• New words? Once beat/bead contrast learned …
Generalize to seat/seed and to tack/tag?
• New speakers? Learn contrast for speakers A & B …
Generalize to C & D?
• New L1 with same cue? Contrast learned for Native Polish speakers of English: Generalize to native Korean?
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Conclusions
Listeners:
– Represent forms other than those they produce
– Process variants depending on prior experience
– Store multiple concrete representations
– Benefit from a canonical form (even if it is not the most frequent)
A listener’s knowledge is not autonomous, but bound by experienceand through experience, multiple representations are promoted
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Thank You!
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Example illustration of priming
-er features
Speech Signal:
FeatureBundles
Phonemes or Phoneme Chunks
Long-termRepresentation
/-er/
//
Prime: slend-er
features
Long-term repetition priming
Target: slend-erPrime: slend-[] Target: slend-[]
/-/
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Error Rates show GA benefit
Error Rates for NY Targets preceded by NY Primes Across Participant Groups
Overt Covert GA
Perc
ent Er
ror
0
5
10
15
20
25
30
RelatedUnrelated
Error Rates for NY Targets Preceded byGA Primes Across Participant Groups
Overt Covert GAPe
rcen
t Er
ror
0
5
10
15
20
25
30
RelatedUnrelated
Error rates collapsed across form priming and long-term priming experiments
Hearing a GA prime improves target recognition accuracy even for Overt-
NYC participants
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– Dialect atlas – (Kurath, 1939; Labov et al., 2006)
– Social factors – (Giles, 1970; Labov, 1972; Preston, 1986)
– Acoustic analysis –– Dialect identification – (Clopper & Pisoni, 2003)
– Dialect variation in OT – (Anttila & Cho, 1998)
– Perceptual learning & speaker adaptation– (Dahan & Scarborough, 2005; Kraljic & Samuel, 2005 ; Norris, McQueen, & Cutler, 2003)– – Perception of merged and unmerged dialects– (Bowie, 2000; Janson & Schulman, 1983; Labov, Karan, & Miller, 1991; )
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Experiment 2: Semantic Priming Schema(Covert-NYC perspective)
features features
Speech Signal:
FeatureBundles
Phoneme
Lexical
//
//
[] [][]
?
Semantic priming
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Coping with variation
White or dark meat?
What was produced? [dk]What did I hear? dog
[dk] ~ [dak] variation not surprising
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Crossing the threshold
What changed?
Do I now treat [dk] as a systematic variant of /dk/?
Did I learn to map a variant (e.g., [dk]) onto an existing representation, or did I create a new exemplar
representation?
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Examining linguistic issues with psycholinguistic tasks: Priming
• What is priming?– Preparing a sound, chunk, word – Benefit on the later recognition of a related stimulus
• What happens in a typical experiment– Prime is presented (e.g., horse)– Prime activates
• Sounds ([h], [o], etc.)• Representation (//)• Meaning horse, barn, cow, etc.
– Measure: Reaction time to target
• Benefits of priming paradigm– Sensitivity to subtle acoustic deviations– Manipulate delay: Immediate (processing) and long-term (representation) effects
Target presentedForm-sharing:
courseIdentical:
horse Meaning-related:
barn
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Example illustration of priming
-er features
Speech Signal:
FeatureBundles
Phonemes or Phoneme Chunks
Long-termRepresentation
/-er/
//
Prime: slend-er
Form priming
Target: slend-er Target: slend-[]
features
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Example illustration of priming
-er features
Speech Signal:
FeatureBundles
Phonemes or Phoneme Chunks
Long-termRepresentation
/-er/
//
Prime: slend-er Target: thin
features
Semantic Priming
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-er features
Speech Signal:
FeatureBundles
Phonemes or Phoneme Chunks
Long-termRepresentation
/-er/
Prime: slend-er
features
Long-term priming
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What’s ahead
• Experiment design and results
• Generalization to within-dialect phonetic variation
• Discussion of models of representation
• Implications and future directions
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What is the comparison?
• Comparison– Reaction time to TARGET preceded by related PRIME to– Reaction time to TARGET preceded by unrelated CONTROL PRIME
Prime Target Reaction Time (Target)Control Trial: runny runn-er 960Critical Trial: runn-er runn-er 880
Difference: 80 msec Priming Effect
Prime Target Reaction Time (Target)Control Trial: runny runn-er 960Critical Trial: run[] runn-er 920
Difference: 40 msec Priming Effect
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Experiment 1: Form priming error rates
Error Rates for NYC Targets Preceded by GA Primes
Overt-NYC Covert-NYC GA
Perc
ent E
rror
0
10
20
30
Hearing a GA prime improves recognition of NYC target
across the board
GA – NYC runn-er – run[]NYC – NYC run[] – run[]
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What can we learn through priming tasks?
Form priming: Do listeners generalize a pattern for cross-dialectal variants independent of dialect?
Semantic priming: Are cross-dialectal variants mapped onto by meaning by listeners independent of dialect?
Long-term repetition priming: Are cross-dialectal variants mapped onto a single abstract representation, or stored as individual concrete, or exemplar, representations?
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