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Record W1619596152 · doi:10.1109/scft.1999.781466

A wideband speech and audio codec at 16/24/32 kbit/s using hybrid ACELP/TCX techniques

2003· article· en· W1619596152 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Compression Techniques
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsSpeech codingComputer scienceSpeech recognitionCodecLinear predictionLinear predictive codingFull RateComputer hardware

Abstract

fetched live from OpenAlex

A hybrid ACELP/TCX algorithm for coding speech and music signals at 16, 24, and 32 kbit/s is presented. The algorithm switches between algebraic code excited linear prediction (ACELP) and transform coded excitation (TCX) modes on a 20-ms frame basis. Applying TCX on 20 ms frames improved the quality for music signals. Special care was taken to alleviate the switching artifacts between the two modes resulting in a transparent switching process. Subjective test results showed that for speech signals, the performance at 16, 24, and 32 kbit/s, is equivalent to G.722 at 48, 56, and 64 kbit/s, respectively. For music signals, the quality at 24 kbit/s was found equivalent to G.722 at 56 kbit/s. However, at 16 kbit/s, the quality for music was slightly lower than G.722 at 48 kbit/s.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.311
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 communication0.0000.001
Open science0.0010.001
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 head0.025
GPT teacher head0.282
Teacher spread0.257 · 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

Quick stats

Citations25
Published2003
Admission routes1
Has abstractyes

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