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Record W4233027766 · doi:10.1109/tasl.2013.2273045

IEEE Transactions on Audio, Speech, and Language Processing publication information

2013· article· en· W4233027766 on OpenAlex
Li Deng, Geoffrey Chan, Pascale Fung Ieee, Dr Prendergast, Thomas Siegert, Business Administration, Matthew Loeb, Douglas Gorham, Eileen Lach, Betsy Davis, Ieee-Usa Chris Brantley, Alexander Pasik, Information Technology, Patrick Mahoney, Cecelia Jankowski, Fran Zappulla, Peter Tuohy, Martin Morahan, Andrew Swartz

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Audio Speech and Language Processing · 2013
Typearticle
Languageen
FieldComputer Science
TopicSpeech Recognition and Synthesis
Canadian institutionsQueen's University
FundersUniversity of Texas at DallasKorea Advanced Institute of Science and TechnologyHong Kong Polytechnic UniversityTsinghua UniversityAalborg UniversitetNanyang Technological UniversityYork UniversityBen-Gurion University of the NegevBar-Ilan UniversityUniversity of CambridgeNational Cheng Kung UniversityInstitut national de recherche en informatique et en automatique (INRIA)Ohio State University
KeywordsComputer scienceSpeech recognitionNatural language processing

Abstract

fetched live from OpenAlex

The Signal Processing Society is an organization, within the framework of the IEEE, of members with principal professional interest in the technology of transmission, recording, reproduction, processing, and measurement of speech and other signals by digital electronic, electrical, acoustic, mechanical, and optical means, the components and systems to accomplish these and related aims, and the environmental, psychological, and physiological factors concerned therewith.

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 categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.988
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
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.004
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 head0.012
GPT teacher head0.241
Teacher spread0.228 · 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