{"id":"W4388039816","doi":"10.1109/eecsi59885.2023.10295651","title":"Speech Emotion Recognition Using Deep Learning Techniques and Augmented Features","year":2023,"lang":"en","type":"article","venue":"","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Speech recognition; Preprocessor; Normalization (sociology); Mel-frequency cepstrum; Cepstrum; Feature extraction; Artificial intelligence; Noise (video); Focus (optics); Pattern recognition (psychology); Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00025411,0.00009687179,0.00009097456,0.0002647026,0.0001434104,0.00003440485,0.00002798794,0.0001415039,0.001235105],"category_scores_gemma":[0.00003084527,0.00009359657,0.00003373554,0.0002938175,0.0000292574,0.0001018383,0.00002421915,0.0001770691,0.00042387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000214043,"about_ca_system_score_gemma":0.000003662555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009205806,"about_ca_topic_score_gemma":0.00002404864,"domain_scores_codex":[0.9992262,0.0001306855,0.0001385686,0.0002302615,0.00009184885,0.0001824433],"domain_scores_gemma":[0.9997219,0.00003789175,0.0000577092,0.00007224137,0.00006229079,0.00004795744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0000322768,0.00004221315,0.0007098448,0.00001830429,0.00002954522,0.00003265754,0.0006632768,0.00000109756,0.00928741,0.0001864412,0.001231662,0.9877653],"study_design_scores_gemma":[0.01220661,0.003314922,0.4350318,0.001542691,0.000765472,0.007210093,0.066485,0.01103372,0.3419303,0.04141925,0.07460889,0.004451245],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9148103,0.00006518511,0.002701555,0.0002512881,0.0004170753,0.0002808032,0.000003194142,0.00127797,0.08019261],"genre_scores_gemma":[0.9724361,0.000273674,0.009271177,0.0003046518,0.000396786,0.00003590764,0.0003885076,0.00005128278,0.0168419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.983314,"threshold_uncertainty_score":0.9996779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05645949516623722,"score_gpt":0.3448737911907646,"score_spread":0.2884142960245274,"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."}}