1. 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

2. 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)

3. 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)

4. 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!

5. 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, unpredictable Noise unpredictable

6. Catherine Caldwell-Harris Boston University 6 of 23 Examples of conditions Predictable ContextTarget His plan meant taking a big risk.Hi Freq Tom fell down and got a bad bruise.Lo Freq Unpredictable Context Bill might discuss the foam. Hi Freq I was considering the crook. Lo Freq

7. 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 > Mandarin High/low frequency of target words Predict: frequency effects will depend on proficiency Age of acquisition Predict: Doesn’t matter, after controlling for proficiency?

8. 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

9. Learning History Variables

13. 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

14. Catherine Caldwell-Harris Boston University 14 of 23 Effect sizes for main effects and interactions

16. Predictable Hi Freq Predictable Lo Freq Unpredictable Hi Freq Unpredictable Lo Freq

17. Spanish L1

18. Russian L1

19. Mandarin L1

20. 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.

21. Learning History Variables

22. 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 confound High/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?

23. 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