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Record W7096793181

DESCRIPTION OF THE FRENCH NATO CANDIDATE

2008· article· en· W7096793181 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Compression Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsIntelligibility (philosophy)Noise reductionCoding (social sciences)Filter (signal processing)Noise (video)Speech enhancementArtificial noiseWiener filter
DOInot available

Abstract

fetched live from OpenAlex

This paper describes the narrow-band speech coder that was proposed by France as a candidate to the new NATO standard STANAG-4591. This dual–rate coder at 1.2 and 2.4 kbps is based on the HSX (Harmonic & Stochastic eXcitation) algorithm.. The 2.4 kbps version was first developed by the University of Sherbrooke [1], then refined by Thales Communications (formerly Thomson-CSF Communications). An extension at 1.2 kbps was later developed by Thales Communications. This half-rate version uses the same algorithmic core than the 2.4 kbps version, but achieves a lower bit rate by grouping 3 consecutive frames grouped into a single 67.5 ms super-frame [2]. A noise reduction procedure is considered as a part of the next NATO low bit rate speech coding standard.. This noise reduction system is based on the combination of two different noise reduction techniques. The first one is the Wiener filter under signal presence uncertainty. The second one is Lim’s filter, that takes into account the auto-regressive model of human voice [3]. These new coders provide a low complexity solution with increased intelligibility and quality compatible with a growing number of military, professional and commercial applications. 1.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.817
Threshold uncertainty score0.158

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 science0.0010.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.250
Teacher spread0.225 · 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 teacher head, not a consensus.

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

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

Citations0
Published2008
Admission routes1
Has abstractyes

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