Raspberry, not a car: Context predictability and a phonological advantage in early and late learners' processing of speech in noise

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Abstract

Second language learners perform worse than native speakers under adverse listening conditions, such as speech in noise (SPIN). No data are available on heritage language speakers' (early naturalistic interrupted learners') ability to perceive SPIN. The current study fills this gap and investigates the perception of Russian speech in multi-talker babble noise by the matched groups of high- and low-proficiency heritage speakers (HSs) and late second language learners of Russian who were native speakers of English. The study includes a control group of Russian native speakers. It manipulates the noise level (high and low), and context cloze probability (high and low). The results of the SPIN task are compared to the tasks testing the control of phonology, AXB discrimination and picture-word discrimination, and lexical knowledge, a word translation task, in the same participants. The increased phonological sensitivity of HSs interacted with their ability to rely on top-down processing in sentence integration, use contextual cues, and build expectancies in the high-noise/high-context condition in a bootstrapping fashion. HSs outperformed oral proficiency-matched late second language learners on SPIN task and two tests of phonological sensitivity. The outcomes of the SPIN experiment support both the early naturalistic advantage and the role of proficiency in HSs. HSs' ability to take advantage of the high-predictability context in the high-noise condition was mitigated by their level of proficiency. Only high-proficiency HSs, but not any other non-native group, took advantage of the high-predictability context that became available with better phonological processing skills in high-noise. The study thus confirms high-proficiency (but not low-proficiency) HSs' nativelike ability to combine bottom-up and top-down cues in processing SPIN.

Figures

  • Table 1 | Background information of the participants in the study.
  • Table 2 | Participants’ mean accuracy scores across all conditions.
  • FIGURE 1 | Accuracy scores on SPIN task in heritage, L2, and native participants. Heritage and L2 participants are divided into high- and low-proficiency groups. The left panel represents the high-noise and the right the low-noise conditions. L2-low – low-proficiency L2 learners, L2-high – high-proficiency L2 learners, HS-low – low-proficiency heritage speakers, HS-high – high-proficiency heritage speakers, and Native – native speakers of Russian.
  • Table 3 | Repeated measures ANOVA results for Experiment 1: speech in noise, by-subject analyses.
  • Table 4 | Repeated measures ANOVA results for Experiment 1: speech in noise, by-item analyses.
  • FIGURE 2 | Context effects in SPIN task for heritage, L2, and native participants. Context effect is calculated as a difference between the score in the high-predictability context condition and low-predictability context condition. 0.5 corresponds to 50% increase in accuracy in the high-predictability condition.
  • FIGURE 3 | AXB discrimination task accuracy scores across all groups.The labels ‘cv’, ‘p’, and ‘t’ represent the three critical conditions, the C’VC-CjVC, final /p–p’/, and /t–t’/ consonants.
  • FIGURE 4 | Heritage, L2, and native participants’ accuracy scores on picture-word discrimination task.

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CITATION STYLE

APA

Gor, K. (2014). Raspberry, not a car: Context predictability and a phonological advantage in early and late learners’ processing of speech in noise. Frontiers in Psychology, 5(DEC). https://doi.org/10.3389/fpsyg.2014.01449

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