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Record W2605474046 · doi:10.1017/s033258651500013x

What do compounds and noun phrases tell us about tonal targets in Finnish?

2015· article· en· W2605474046 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

VenueNordic Journal of Linguistics · 2015
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of Alberta
FundersItä-Suomen Yliopisto
KeywordsStress (linguistics)Intonation (linguistics)LinguisticsNoun phraseNounPhraseInterpretation (philosophy)PerceptionPitch accentFlexibility (engineering)Computer scienceProsodyNatural language processingSpeech recognitionPsychologyMathematicsPhilosophy

Abstract

fetched live from OpenAlex

This article compares three accounts of Finnish intonation using a perception experiment with manipulated f0 contours. The experiment involved compound/noun phrase minimal pairs differing in f0 pattern. To address the question of tonal specification, manipulations changed f0 contours of recorded compound words, associating them with f0 patterns having different components of the naturally occurring f0 rise-fall contour. Thus, the study investigated which tonal targets were crucial for the perception of a complete tonal contour inducing a noun phrase interpretation. Results suggested that the falling part of the rise-falls, modelled as realisations of a high and a following low target, was essential. They furthermore revealed evidence for these targets being associated with prosodic phrases, as well as for Finnish tonal targets being characterised by a flexibility that contrasts with accent realisations in languages like English.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.515

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.057
GPT teacher head0.379
Teacher spread0.322 · 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