{"id":"W3210574093","doi":"10.1109/icassp43922.2022.9747908","title":"Temporal Knowledge Distillation for on-device Audio Classification","year":2022,"lang":"en","type":"article","venue":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","topic":"Music and Audio Processing","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hyperion Technologies (Canada)","funders":"","keywords":"Computer science; Leverage (statistics); Inference; Distillation; Transformer; Artificial intelligence; Machine learning; Mobile device","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009623696,0.0004154539,0.0003836822,0.0004203027,0.001264047,0.0008930993,0.001288627,0.00012329,0.0004727426],"category_scores_gemma":[0.0001699712,0.0004231329,0.0001296604,0.000530477,0.0001546724,0.0005933594,0.0003478175,0.0007528953,0.00003725182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004218883,"about_ca_system_score_gemma":0.0006261137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001345841,"about_ca_topic_score_gemma":0.000006365874,"domain_scores_codex":[0.9962878,0.0001574539,0.0006842971,0.001148954,0.001216184,0.0005053391],"domain_scores_gemma":[0.9977809,0.0003398021,0.0006182309,0.0003864074,0.0006545717,0.0002201429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006412506,0.001285209,0.0006401369,0.0003664913,0.0001638611,0.0001001738,0.001857365,0.003044959,0.0696234,0.07571533,0.03766941,0.8088924],"study_design_scores_gemma":[0.000987181,0.0005863758,0.0006739508,0.0001549397,0.00003988363,0.00006570464,0.0005785125,0.9617474,0.001102137,0.01320768,0.0202035,0.0006527164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02503799,0.0003455584,0.9404016,0.01073008,0.002717639,0.000828754,0.0003488155,0.0004035159,0.01918605],"genre_scores_gemma":[0.9847661,0.00004097693,0.009707558,0.001350062,0.0006594328,0.0002265283,0.0001749273,0.00004304135,0.003031333],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9597281,"threshold_uncertainty_score":0.999822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09714030047451612,"score_gpt":0.3364499120998716,"score_spread":0.2393096116253555,"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."}}