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Record W1571655072

The acoustics and articulation of mandarin sibilants: Improving our data by modeling the palate with EMA

2011· article· en· W1571655072 on OpenAlexaffvenue
Chris Neufeld, Andrei Anghelescu

Bibliographic record

VenueCanadian acoustics · 2011
Typearticle
Languageen
FieldComputer Science
TopicSpeech and Audio Processing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPlace of articulationMandarin ChineseArticulation (sociology)AcousticsCogMathematicsSpeech recognitionComputer sciencePhysicsLinguisticsArtificial intelligenceConsonantVowel
DOInot available

Abstract

fetched live from OpenAlex

Electromagnetic articulography (EMA) is a tool for tracking the motion of the articulators during speech. Mandarin has a three-way place contrast for sibilants: alveolar, palatal and retmflex. For each place there are three possible manners of articulation: fricatives, unaspirated aifricates and aspirated aifricates. Place of articulation (PoA) of Mandarin Sibilants is readily distinguished by peak COG. For all manners of articulation, alveolar sibilants had the highest COG, retroflex the lowest, and palatal in the middle. Manner of articulation is distinguished by the relative time of the COG peak. The constriction location (cl) and constriction degree (cd) of the tongue tip (TT) and tongue body (TB) coils were calculated using this model. At each sample, the shortest line in the sagittal plane between the tongue coil and the palate model was found.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.035
GPT teacher head0.222
Teacher spread0.188 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2011
Admission routes2
Has abstractyes

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