{"id":"W174187144","doi":"10.1007/978-3-540-49127-9_51","title":"Time Delay Estimation and Source Localization","year":2007,"lang":"en","type":"book-chapter","venue":"Springer handbooks","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Computer science; Estimator; Algorithm; Reverberation; Microphone array; Microphone; Interpolation (computer graphics); Cross-correlation; Wideband; Speech recognition; Mathematics; Acoustics; Statistics; Telecommunications; Electronic engineering; Engineering; Frame (networking)","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":[0.0002298741,0.0002610794,0.0002278244,0.0002151531,0.0001780704,0.0002529142,0.0002992029,0.0002546523,0.0000439123],"category_scores_gemma":[0.0000160105,0.0002638749,0.00005341114,0.00003259402,0.00009569807,0.000241981,0.0002151697,0.0002172768,0.0002714168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005268257,"about_ca_system_score_gemma":0.0000625766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002299921,"about_ca_topic_score_gemma":0.000003887124,"domain_scores_codex":[0.9987218,0.000006440723,0.0002605728,0.000467252,0.0003043602,0.000239587],"domain_scores_gemma":[0.9992144,0.00003827688,0.000195466,0.0003507936,0.00008546874,0.0001155899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007015936,0.000006420609,0.00001178285,0.00008228888,0.00003348708,0.00003871127,0.0004492399,0.0003216967,0.000316698,0.0108247,0.0005124058,0.9873956],"study_design_scores_gemma":[0.001140109,0.0002128293,0.00003105642,0.002799094,0.0001412074,0.0003017338,0.000006530037,0.3402477,0.04861457,0.06995665,0.5342452,0.002303337],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.00004997714,0.001324274,0.8094926,0.00003603596,0.0001153933,0.000114275,7.519822e-7,0.0002282837,0.1886384],"genre_scores_gemma":[0.00370793,0.0001644678,0.1918067,0.00124897,0.0005116464,0.000007642396,0.00002716185,0.0001343568,0.8023911],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9850922,"threshold_uncertainty_score":0.9999813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01623198841537726,"score_gpt":0.228524915140932,"score_spread":0.2122929267255547,"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."}}