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Record W2349511812

Design of Speech Signal Processor for Cochlear Implants

2008· article· en· W2349511812 on OpenAlexvenueno aff
Xiao Ling

Bibliographic record

VenueMicrocomputer applications · 2008
Typearticle
Languageen
FieldEngineering
TopicInertial Sensor and Navigation
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceVoice activity detectionSpeech recognitionEncoderInterface (matter)Sampling (signal processing)SIGNAL (programming language)TransmitterChannel (broadcasting)Speech processingSpeech codingTelecommunicationsDetector
DOInot available

Abstract

fetched live from OpenAlex

Cochlea implants is an artificial setting using external body worn speech processor and internal receiver-stimulator for stimulating remaining auditory nerve that enables understanding the speech by hearing impaired personnel.Development of the Speech Processor of Cochlear implants is based on TMS320VC5502 is described.The system comprises sampling interface,radio frequency transmitter interface.The low power stereo A/D CS53L21 is used to collect the speech signal,The MLX90121 is used to as data encoder to send speech information to receiver/stimulator via RF link;A four-channel CIS(Continuous Interleaved Sampling)algorithm is implemented for the speech processor.The implementation aspects of CIS algorithm are validated using the test data of speech samples.

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: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.588
Threshold uncertainty score0.332

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 head0.019
GPT teacher head0.226
Teacher spread0.207 · 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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