{"id":"W1565000507","doi":"10.1109/icassp.2015.7178921","title":"Multi-lingual speech recognition with low-rank multi-task deep neural networks","year":2015,"lang":"en","type":"article","venue":"","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Speech recognition; Task (project management); Artificial neural network; Deep neural networks; Rank (graph theory); Artificial intelligence; Time delay neural network; Deep learning; Natural language processing; Pattern recognition (psychology); Mathematics; Engineering","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":[0.000415724,0.0002532052,0.0002390382,0.0001476552,0.0001188215,0.0002799657,0.0005520573,0.0001315904,0.0001307815],"category_scores_gemma":[0.0001464674,0.0001972233,0.00008530889,0.0004683204,0.00006685548,0.0007123118,0.0001241348,0.0002352204,0.0004939858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005384488,"about_ca_system_score_gemma":0.0000548209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001076285,"about_ca_topic_score_gemma":0.0004665857,"domain_scores_codex":[0.9981462,0.0001378891,0.0002995061,0.0005644227,0.0003904905,0.0004615156],"domain_scores_gemma":[0.9985672,0.0001236096,0.0001088321,0.0004528155,0.0003815447,0.0003660122],"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":[0.00004239559,0.0002766669,0.0004814585,0.000005787963,0.00002851734,0.000152936,0.000365803,0.0003746515,0.0001205579,0.00001799071,0.0003694632,0.9977638],"study_design_scores_gemma":[0.001949342,0.0001385143,0.0007097808,0.00002417589,0.00001594505,0.000206752,0.0002295239,0.9907641,0.00522188,0.00007791579,0.0002570754,0.0004049894],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07207038,0.00007048524,0.9237382,0.0003346967,0.0006072402,0.0002981394,0.000003084113,0.0005901242,0.002287587],"genre_scores_gemma":[0.3931225,0.000008558476,0.6050326,0.001169192,0.0001707194,0.00002414344,0.00001899156,0.00002309795,0.0004301398],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9973588,"threshold_uncertainty_score":0.8042535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05531093932739749,"score_gpt":0.266749287209576,"score_spread":0.2114383478821785,"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."}}