{"id":"W4404239327","doi":"10.1109/indiscon62179.2024.10744282","title":"Speech Emotion Recognition System based on Auto Encoder","year":2024,"lang":"en","type":"article","venue":"","topic":"Wireless Sensor Networks and IoT","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Speech recognition; Computer science; Emotion recognition; Encoder; Speaker recognition; Autoencoder; Artificial intelligence; Artificial neural network","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002867245,0.0003142995,0.0004296014,0.0003462074,0.0001570743,0.0004715223,0.0004002885,0.0002501445,0.004853185],"category_scores_gemma":[0.000477067,0.0001382189,0.0001977644,0.0001692934,0.00009418486,0.0004464215,0.0002595445,0.0002754091,0.001861472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000153527,"about_ca_system_score_gemma":0.0002180769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001191232,"about_ca_topic_score_gemma":0.001035715,"domain_scores_codex":[0.9997472,0.00003009283,0.00002313458,0.00007442239,0.0001021563,0.00002306131],"domain_scores_gemma":[0.9996774,0.00006538785,0.00002014482,0.00002965101,0.0001902694,0.00001713755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008416722,0.0002367825,0.002990799,0.0002666939,0.00006122831,0.0003764799,0.000232075,0.004991942,0.4136233,0.002161417,0.007738176,0.5664796],"study_design_scores_gemma":[0.0001519097,0.001038164,0.01500991,0.00007693037,0.0002133055,0.002066818,0.0001330078,0.5623733,0.396879,0.001245405,0.02070718,0.0001050936],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1995887,0.001208809,0.7634364,0.0002965725,0.0004053793,0.000330456,0.0009045549,0.01888459,0.0149445],"genre_scores_gemma":[0.7655405,0.0007271714,0.2046273,0.0003924374,0.0001657342,0.0002895135,0.001694164,0.00019437,0.02636879],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004853185,"threshold_uncertainty_score":0.01623553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01191190218767718,"score_gpt":0.1949383509298237,"score_spread":0.1830264487421465,"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."}}