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Record W2807416114 · doi:10.1159/000484611

Stress-Induced Acoustic Variation in L2 and L1 Spanish Vowels

2018· article· en· W2807416114 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhonetica · 2018
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVariation (astronomy)Stress (linguistics)LinguisticsSpeech recognitionPsychologyAcoustic phoneticsAudiologyAcousticsPhoneticsComputer sciencePhysicsMedicinePhilosophy

Abstract

fetched live from OpenAlex

AIM: We assessed the effect of lexical stress on the duration and quality of Spanish word-final vowels /a, e, o/ produced by American English late intermediate learners of L2 Spanish, as compared to those of native L1 Argentine Spanish speakers. METHODS: Participants read 54 real words ending in /a, e, o/, with either final or penultimate lexical stress, embedded in a text and a word list. We measured vowel duration and both F1 and F2 frequencies at 3 temporal points. RESULTS: stressed vowels were longer than unstressed vowels, in Spanish L1 and L2. L1 and L2 Spanish stressed /a/ and /e/ had higher F1 values than their unstressed counterparts. Only the L2 speakers showed evidence of rising offglides for /e/ and /o/. The L2 and L1 Spanish vowel space was compressed in the absence of stress. CONCLUSION: Lexical stress affected the vowel quality of L1 and L2 Spanish vowels. We provide an up-to-date account of the formant trajectories of Argentine River Plate Spanish word-final /a, e, o/ and offer experimental support to the claim that stress affects the quality of Spanish vowels in word-final contexts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.945
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.036
GPT teacher head0.350
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it