{"id":"W2134122649","doi":"10.1109/icassp.2007.367259","title":"A Robust Pitch Estimation Algorithm in Noise","year":2007,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Pitch detection algorithm; Algorithm; Noise (video); Computer science; Range (aeronautics); Speech recognition; Frequency domain; Impulse (physics); Harmonic; Impulse noise; SIGNAL (programming language); Harmonic analysis; Acoustics; Mathematics; Speech processing; Physics; Artificial intelligence; Engineering; Computer vision; Pixel","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":[],"consensus_categories":[],"category_scores_codex":[0.0003345077,0.00004983208,0.00005246352,0.0001022459,0.00003361538,0.0000857029,0.0002268885,0.00002689266,0.00001308287],"category_scores_gemma":[0.00002123462,0.00004389129,0.00001250015,0.0004098954,0.000008202505,0.0004583967,0.00005165464,0.00005640618,0.00005612947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002900945,"about_ca_system_score_gemma":0.00002795204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000311786,"about_ca_topic_score_gemma":0.00003495888,"domain_scores_codex":[0.9994103,0.000005204027,0.0001202217,0.0001558996,0.000124262,0.0001841272],"domain_scores_gemma":[0.999743,0.00002779971,0.00002496543,0.0001361864,0.00002422578,0.00004382666],"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":[5.470852e-7,0.00002136074,0.0005078275,0.000002519576,5.195775e-7,0.00001847783,0.0001295732,0.0005103352,0.0006376847,0.0004084217,0.0001207134,0.997642],"study_design_scores_gemma":[0.0003402377,0.00002398002,0.01577671,0.00002507406,7.762395e-7,0.00002434626,0.0000352242,0.8456071,0.1335617,0.00414343,0.0003035153,0.0001578253],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01155549,0.00003481538,0.9799664,0.0003849258,0.00008687011,0.00003828376,5.059212e-8,0.0001063265,0.007826822],"genre_scores_gemma":[0.147192,0.000001107623,0.8522197,0.0003097074,0.00002425295,0.000001106663,4.225983e-7,0.000002185509,0.000249513],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9974842,"threshold_uncertainty_score":0.1789835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01891106418720008,"score_gpt":0.2518649321198302,"score_spread":0.2329538679326302,"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."}}