catherine caldwell-harris boston university 1 speech perception by non-native speakers declines...
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Catherine Caldwell-Harris Boston University
1
Speech Perception by Non-Native Speakers Declines Drastically in
Noisy Conditions
Catherine Caldwell-Harris,Inna Ryvkin, Andrei Anghelescu,
Loraine K. Obler
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Catherine Caldwell-Harris Boston University 2 of 23
Expert language processing system
cleans up noisy input -- Wow!
Highly fluent speakers• Fill in from meaning• Are more sensitive to auditory cues
(Barbara Shinn-Cunninghams’ talk)
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Catherine Caldwell-Harris Boston University 3 of 23
We already know a lot about factors influencing non-native speech
perception
‘Fluency/ability’ matters; and these factors influence fluency (in order of strength):
• Proficiency• Number of years of language use • Amount and type of current use• Age of acquisition (often determines above factors)
Task and input factors• Noise / environment• Sentence context (predictability of words)
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Catherine Caldwell-Harris Boston University 4 of 23
But much less is known about:
How factors that influence skill level interact
• Is early acquisition important even controlling for proficiency and current use?
Does word frequency matter? How do input factors interact?
• Examine word freq in high/low predictable context
Similarity between first and second language
• Those great Dutch learners of English!
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Catherine Caldwell-Harris Boston University 5 of 23
Speech Perception In Noise Test (Bilger, 1984)
Participants were instructed to repeat the last word of each sentence.
80 items selected from the original SPIN sentences.Three variables, fully crossed: predictability of target (Predictable/Unpredictable) lexical frequency of target (High/Low) noise (Noise/Clear).
The noise consisted of multi-speaker babble. Signal-to-noise ratio was -2dB for sentence-plus-noise items. Each item is a sentence that was prerecorded by an adult male and
presented in stereo through headphones.
Clear, predictable Noise, predictable Clear, unpredictableNoise unpredictable
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Catherine Caldwell-Harris Boston University 6 of 23
Examples of conditions
Predictable Context Target
His plan meant taking a big risk. Hi FreqTom fell down and got a bad bruise. Lo Freq
Unpredictable ContextBill might discuss the foam. Hi Freq I was considering the crook. Lo Freq
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Catherine Caldwell-Harris Boston University 7 of 23
Questions in Current Study
Similarity between first and second language
• With L1 Spanish, Russian, Mandarin When identifying targets in spoken English
• Predict: Spanish > Russian > MandarinHigh/low frequency of target words• Predict: frequency effects will depend on
proficiencyAge of acquisition• Predict: Doesn’t matter, after controlling for
proficiency?
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Catherine Caldwell-Harris Boston University 8 of 23
Procedure
Questionnaire Language History Self-rating of proficiency in L1 and English Adult English Language Use Scale (AELU)
Hearing Threshold determination SPIN meant to be administered 50dB above
hearing threshold. Threshold tested via a Behringer UB502
Eurorack 5 Input Mixer
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ENGLISH MANDARIN RUSSIAN SPANISH StatisticalDifferences
Total 25 20 20 20Age 21 21 20 23 n.s.
Verbal SAT 677 570 657 559 (Eng=Rus) >(Mand=Span)
Age ofArrival
14.7 8.3 11.1 Mandarinlatest
Years in US 5.8 11.3 9.8 Mandainfewest
Age ofLearningOnset
10.0 7.5 6.5 Mandarinlatest
AdultEnglish UseScale
20.7(21 totalpossible)
12.3 14.3 13.10 Mandarinleast
Learning History Variables
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0
10
20
30
40
50
60
70
80
90
100
Clear Noise Clear Noise
English Mandarin
Predictable, HighFreqPredictable, LowFreqUnpredictable, High FreqUnpredictable, Low Freq
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0
10
20
30
40
50
60
70
80
90
100
Clear Noise Clear Noise
English Mandarin
Predictable, HighFreqPredictable, LowFreqUnpredictable, High FreqUnpredictable, Low Freq
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0
10
20
30
40
50
60
70
80
90
100
Clear Noise Clear Noise
Russian Spanish
Predictable HighPredictable LowUnpredictable HighUnpredictable Low
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Catherine Caldwell-Harris Boston University 13 of 23
Overview of Results
Native English-speakers performed nearly at ceiling, Mandarin speakers performed most poorly, and Spanish- and Russian-speakers show in intermediate results.
Noise, predictability, frequency matter for all speakers
BUT: Lexical frequency of target is a small effect of native English speakers
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Catherine Caldwell-Harris Boston University 14 of 23
Effect sizes for main effects and interactions
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Clear Condition
-5
10
25
40
55
70
85
100
-5 5 15 25 35
Age of Arrival in the U.S.
Percentage of Targets Correct
Predictable - High Freq
Predictable - Low Freq
Unpredictable - High Freq
Unpredictable - Low Freq
Poly. (Predictable - HighFreq)
Poly. (Predictable - LowFreq)
Poly. (Unpredictable - HighFreq)Poly. (Unpredictable - LowFreq)
(Native Eng)
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Noise Condition
-5
10
25
40
55
70
85
100
-5 5 15 25 35
Age of Arrival in the U.S.
Percentage of Targets Correct
(Native Eng)
Predictable Hi Freq
Predictable Lo Freq
Unpredictable Hi Freq
Unpredictable Lo Freq
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Noise Condition
-5
10
25
40
55
70
85
100
0 5 10 15 20 25 30 35
Age of Arrival in the U.S.
Percentage of Targets Correct
Predictable - High Freq
Predictable - Low Freq
Unpredictable - High Freq
Unpredictable - Low Freq
Linear (Predictable - HighFreq)Linear (Predictable - LowFreq)Linear (Unpredictable - HighFreq)Linear (Unpredictable - LowFreq)
Spanish L1
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Russian L1
Noise Condition
-5
10
25
40
55
70
85
100
-5 0 5 10 15 20
Age of Arrival in the U.S.
Percentage of Targets Correct
Predictable - High Freq
Predictable - Low Freq
Unpredictable - High Freq
Unpredictable - Low Freq
Linear (Predictable - HighFreq)Linear (Predictable - LowFreq)Linear (Unpredictable - HighFreq)Linear (Unpredictable - LowFreq)
(Native Eng)
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Mandarin L1Noise Condition
-5
10
25
40
55
70
85
100
0 5 10 15 20 25 30 35
Age of Arrival in the U.S.
Percentage of Targets Correct
Predictable - High Freq
Predictable - Low Freq
Unpredictable - High Freq
Unpredictable - Low Freq
Linear (Predictable - HighFreq)Linear (Predictable - LowFreq)Linear (Unpredictable - HighFreq)Linear (Unpredictable - LowFreq)
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Catherine Caldwell-Harris Boston University 20 of 23
Need more participants to determine cline of Spanish >
Russian > Mandarin
Statistically, group differences greatly diminished when ages-of-arrival are taken into account.
Age-of-arrival effects very strong. Why?Age-of-arrival may organize immigrants’ language
learning environment (Caldwell-Harris et al, under review). Still,plots for language groups show steeper slope
for decline in target word detection with age-of-arrival for Mandarin speakers.
But Mandarin group had on average later age-of-arrival.
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ENGLISH MANDARIN RUSSIAN SPANISH StatisticalDifferences
Total 25 20 20 20Age 21 21 20 23 n.s.
Verbal SAT 677 570 657 559 (Eng=Rus) >(Mand=Span)
Age ofArrival
14.7 8.3 11.1 Mandarinlatest
Years in US 5.8 11.3 9.8 Mandainfewest
Age ofLearningOnset
10.0 7.5 6.5 Mandarinlatest
AdultEnglish UseScale
20.7(21 totalpossible)
12.3 14.3 13.10 Mandarinleast
Learning History Variables
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Catherine Caldwell-Harris Boston University 22 of 23
Answers in Current Study
Similarity between first and second language
• Comparing L1 Spanish, Russian, Mandarin• Confirmed: Spanish > Russian > Mandarin• But: age-of-arrival confoundHigh/low frequency of target words• Confirmed: frequency effects depend on
proficiency• Implies ‘subject/experienced’ proficiency is what
matters for processing. For high proficiency speakers, need very low freq words? Is log transform sufficient?
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Catherine Caldwell-Harris Boston University 23 of 23
Second language learning ideal for neural net modeling
Use modeling to clarify proposals about main effects and interactions of:
• The role of frequency (why frequency effects disappear for high proficiency learners)
• Predictability -- test hypotheses about when lower proficiency learners can use context to make predictions
• Vary L1-L2 similarity in simulations• Vary “age of exposure” and intensity of
language contact