L1 Vietnamese L2 English Speakers’ Cues to the Perception of Stress
Bibliographic record
Abstract
L1 transfer affects the process of L2 acquisition in a significant way, \nboth in perception and production, as learners have a tendency to \napply phonological patterns of their native language to the target \nlanguage. This study investigates the extent to which Vietnamese \nnative speakers rely on F0 as a primary cue to perceive stress in \nEnglish nonce words by manipulating the pitch contour around the \nstressed syllable by creating different environments where such pitch \ncontours are realized, and subsequently measuring the differences \nin performance of stress location matching as a result. While the \nacoustic correlates of stress in English are F0, duration, intensity, and \nvowel quality (Fry, 1955; Libermann, 1960), the acoustic correlates of \ntone in Vietnamese are F0, duration, and voice quality (Pham, 2000; \nNguyen & Edmonton, 1997). Despite some overlapping of acoustic \ncorrelates, English lexical stress prediction cannot be predicated on \npitch alone. For example, in a rising tonal contour context such \nas that of a yes/no question (L*H-H%), English stressed syllable \nactually receives a low pitch accent (Pierrehumbert, 1980). \nThe independent variables of this study are stress location in a nonce \nword, the number of syllables in the stimuli, and the type of intonation context where a statement context corresponds to a falling \nintonation pattern and a yes/no question context corresponds to a \nrising intonation pattern. The dependent variable of this study is the \nnumber or percentage of correct responses the participants give to a \nperceptual matching task. To avoid lexical retrieval and memorization \neffect, the nonce words were selected based on a search in a pronunciation corpus of American English. The nonce words have the same \nsyllable shape as a real English word, follow English phonotactics, \nand are controlled for factors such as tendency of vowel reduction. \nBesides the nonce word items, a set of filler items was included in \nthe test instrument, ranging from tokens that are minimal segmental contrast pairs to tokens that differ by syllable length. The experiment \nwas repeated for a control group of L1 American English speakers. \nThe token set was recorded by a native American English speaker, \nrandomized during the actual experiment in blocks, and distributed \nto the participants in different test lists following the Latin square \ndesign. The participants listened to the stimuli with varying stress \nlocations three times and then listened to the stimuli with either a \nstatement or yes/no question intonation. They were asked to identify \nthe sound that they heard previously which matches the sound they \nhave just heard. Similar to Ou’s (2010) findings, the prediction for \nthis study was that L1 Vietnamese L2 English speakers would show \na significant difference in perceiving stress compared to the control \ngroup when the word has a yes/no intonation contour, because of \nVietnamese speakers’ tendency to rely on F0 as an acoustic cue for \ntone perception. \nA mixed repeated measures ANOVA with a between subject factor was conducted. A statistically significant difference in stress \nmatching accuracy between the control and the experimental group \nwas found in the disyllabic-word category. Both sentence types and \nstress location have main effects on the stress matching accuracy, and \nthere is an interaction between the L1 factor and sentence type, as \nwell as between L1 and stress location. Followed-up independent \nsamples t-tests with Bonferroni correction show that the source of \nthe interaction is in the question condition and the word-initial stress \ncondition across the two groups. This is fully in agreement with \nthe prediction that we would see a difference in the stress matching \naccuracy between the L1 English speakers and L1 Vietnamese speakers in word-initial stress condition with a question intonation. No \nsignificant difference was found in the stress matching accuracy of \ntrisyllabic words. The age of arrival factor was also analyzed and \nalthough there was a negative correlation between age of arrival and \nbetter performance at the stress matching task, this relationship was \nnot statistically significant.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".