{"id":"W2810206268","doi":"10.1109/icpcsi.2017.8392033","title":"Design and implementation of a sign-to-speech/text system for deaf and dumb people","year":2017,"lang":"en","type":"article","venue":"2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI)","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Patient Safety Institute","keywords":"Gesture; Sign language; Interpreter; Computer science; American Sign Language; Gesture recognition; Sign (mathematics); Assistive technology; Wired glove; Speech synthesis; Human–computer interaction; Manual communication; Multimedia; Speech recognition; Artificial intelligence; Linguistics; Programming language","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004515929,0.0004360178,0.0006169639,0.0004835922,0.0005096261,0.0009017496,0.001228086,0.0009368944,0.007977316],"category_scores_gemma":[0.0005105369,0.000315495,0.0003742449,0.0001461261,0.0002895625,0.0006132936,0.0007544053,0.000610309,0.003525224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002940746,"about_ca_system_score_gemma":0.0008403359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009537662,"about_ca_topic_score_gemma":0.0007752251,"domain_scores_codex":[0.9995096,0.00005651436,0.00004897902,0.00009068572,0.0002187572,0.00007544966],"domain_scores_gemma":[0.9996846,0.00003273994,0.00002350244,0.00003574891,0.0001497202,0.00007376949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006144529,0.0004420185,0.004213895,0.0008831021,0.0001212918,0.003319446,0.002606228,0.008102414,0.6299714,0.009664734,0.009669643,0.3303915],"study_design_scores_gemma":[0.0004061901,0.003882023,0.01321771,0.0003736423,0.0003840354,0.006863371,0.001513576,0.1884497,0.5360325,0.003446804,0.2451669,0.0002635069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08511026,0.0003800162,0.883138,0.0003704307,0.000339144,0.001179635,0.0002562639,0.01210756,0.01711879],"genre_scores_gemma":[0.4796886,0.0003513089,0.4837919,0.0003800312,0.00005654875,0.0009241724,0.0003802419,0.0005414397,0.03388578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007977316,"threshold_uncertainty_score":0.02668673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03490298165725236,"score_gpt":0.3038201683756176,"score_spread":0.2689171867183653,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}