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Record W2125160547 · doi:10.1109/icassp.1984.1172695

Implementation of a full duplex 2.4 kbps LPC vocoder on a single TMS-320 microprocessor chip

2005· article· en· W2125160547 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 institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsMicroprocessorComputer scienceChipComputer hardwareDigital signal processorDigital signal processingLinear predictive codingEmbedded systemSpeech codingSpeech recognitionTelecommunications

Abstract

fetched live from OpenAlex

With the commercial availability of high speed digital signal processors, it is now possible to implement all the linear predictive coding (LPC) tasks (excluding D-A/A-D conversion) on a single chip. In this paper, a very small, high quality, full-duplex, 10th order 2.4 kbps LPC vocoder is described. A single Texas Instruments TMS-320 microprocessor performs LPC analysis, pitch detection, synthesis, and data I/O. At the time of writing this paper, a total of 20 off-the-shelf integrated circuits were used occupying two thirds of a 14cm × 18cm wirewrap board (excluding power supply). The total power dissipation is less than 2 watts. The chip count may be reduced by a factor of two by combining the random logic on a semi-custom integrated circuit. When produced commercially, the cost of this vocoder should be considerably less than existing LPC units.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.481
Threshold uncertainty score0.530

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 science0.0010.000
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 head0.022
GPT teacher head0.316
Teacher spread0.294 · 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

Citations9
Published2005
Admission routes1
Has abstractyes

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