{"id":"W4416749204","doi":"10.1109/iros60139.2025.11247033","title":"Sound Source Localization for Human-Robot Interaction in Outdoor Environments","year":2025,"lang":"","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke; Defence Research and Development Canada","funders":"","keywords":"Acoustic source localization; Microphone; Noise-canceling microphone; Microphone array; Sound localization; Echo (communications protocol); SIGNAL (programming language); Robot; Directional sound","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":[0.0003550893,0.0002377605,0.000244244,0.0003450417,0.0004019458,0.0005770598,0.0005024302,0.0001485131,0.00009146876],"category_scores_gemma":[0.00007630333,0.0002547298,0.00009496663,0.0005643123,0.00006986853,0.0009656097,0.0002555899,0.0001756835,0.00005390732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003023825,"about_ca_system_score_gemma":0.00007831786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000059608,"about_ca_topic_score_gemma":0.0001346658,"domain_scores_codex":[0.9979863,0.00006105696,0.0006006199,0.0006986987,0.0002124437,0.0004409298],"domain_scores_gemma":[0.9992473,0.00009476148,0.0001956835,0.0003611497,0.00003597713,0.00006509272],"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":[0.0001043043,0.0009529845,0.01670994,0.0004475625,0.00008662614,0.000005138391,0.003333668,0.05183147,0.02828381,0.004418143,0.00144289,0.8923835],"study_design_scores_gemma":[0.002839295,0.0002408372,0.002441607,0.0006891089,0.00005108814,0.000004535376,0.0008915924,0.6282963,0.2976107,0.02973671,0.03653314,0.000665041],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01190343,0.0002314765,0.9829027,0.0008040453,0.0008961365,0.0004766978,8.158501e-7,0.00004934362,0.00273536],"genre_scores_gemma":[0.9680899,0.00002151606,0.01262658,0.001410842,0.00009159688,0.0000439629,0.000009882697,0.00001398639,0.01769172],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9702761,"threshold_uncertainty_score":0.9999905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0285226814495932,"score_gpt":0.3159866415101362,"score_spread":0.287463960060543,"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."}}