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Record W2810206268 · doi:10.1109/icpcsi.2017.8392033

Design and implementation of a sign-to-speech/text system for deaf and dumb people

2017· article· en· W2810206268 on OpenAlex
G. Sabaresh, Anitha Karthi

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venue2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI) · 2017
Typearticle
Languageen
FieldComputer Science
TopicHand Gesture Recognition Systems
Canadian institutionsnot available
FundersCanadian Patient Safety Institute
KeywordsGestureSign languageInterpreterComputer scienceAmerican Sign LanguageGesture recognitionSign (mathematics)Assistive technologyWired gloveSpeech synthesisHuman–computer interactionManual communicationMultimediaSpeech recognitionArtificial intelligenceLinguisticsProgramming language

Abstract

fetched live from OpenAlex

This paper shows an approach for outlining and executing a savvy glove for hard of hearing and unable to speak individuals. There have been a few looks into done keeping in mind the end goal to locate a less demanding route for non-vocal individuals to speak with vocal individuals and convey what needs be to the hearing scene. Advancements have been made in gesture based communication yet basically in American Sign Language. This exploration plans to build up a communication via gestures interpreter in view of savvy glove interfaced remotely with microcontroller and content/voice showing gadgets. An approach has been created and modified to hear the gesture based communication. The entire framework has been executed, customized, cased and tried with great outcomes.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.815
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.035
GPT teacher head0.304
Teacher spread0.269 · 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