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Record W2165003351 · doi:10.1109/ccece.2005.1556919

Design of pc-programmable digital hearing-testing device

2006· article· en· W2165003351 on OpenAlexaff
Jignesh Patel, Z. Abid

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Adaptive Filtering Techniques
Canadian institutionsWestern University
Fundersnot available
KeywordsUSBComputer scienceHeadphonesDemodulationCMOSUniversal asynchronous receiver/transmitterElectronic engineeringComputer hardwareSignal generatorPulse-width modulationFilter (signal processing)ChipElectrical engineeringEngineeringVoltageSoftware

Abstract

fetched live from OpenAlex

The design of PC programmable digital hearing-testing device is described in this paper targeting the testing of hearing impairedness in a laboratory environment. It is used to measure the response of each ear at different frequencies and at different sound pressure level (SPL). The device input is the serial 12-bit data and 7-bit control signal from USB connection while the output signal is sound waves with frequency range from 20 Hz to 20 KHz. This device is designed and simulated in 0.18 mum CMOS technology. It is composed of digital components except for the active filter. The device is designed as a single chip to fit on a 32 Omega headphones and powered by 1.3 V supply. The device is designed without using any ADC and DAC converters. Improved designs of 12-bit counter, clock generator and control are proposed. PWM generator is designed using digital components only to provide more accuracy and reliability. A second order, Butter-worth active low-pass filter is used as demodulator. The SPL output of the device is PC controllable through the USB connection

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.612
Threshold uncertainty score0.463

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 science0.0000.000
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 head0.048
GPT teacher head0.238
Teacher spread0.190 · 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 designSimulation or modeling
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
Published2006
Admission routes1
Has abstractyes

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