{"id":"W2071643874","doi":"10.1109/slt.2014.7078552","title":"Incremental translation using hierarchichal phrase-based translation system","year":2014,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machine translation; Computer science; Decoding methods; Speech translation; Transfer-based machine translation; Translation (biology); Phrase; Natural language processing; Artificial intelligence; Speech recognition; Synchronous context-free grammar; Example-based machine translation; Algorithm","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006482095,0.0006421437,0.0007749503,0.001030227,0.0005766521,0.0009066638,0.001131582,0.0008126163,0.004705294],"category_scores_gemma":[0.001734965,0.0003243913,0.0006879531,0.001401782,0.0003851095,0.001089287,0.001073186,0.0008186072,0.003502385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003929128,"about_ca_system_score_gemma":0.001099261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002322003,"about_ca_topic_score_gemma":0.003005701,"domain_scores_codex":[0.9992808,0.0001829231,0.00006916244,0.0001911305,0.0002202796,0.00005572633],"domain_scores_gemma":[0.9990979,0.0002771486,0.00006457849,0.0002346099,0.0002869409,0.00003884497],"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":[0.0005842802,0.0002581516,0.001645088,0.0005856593,0.0001201489,0.0009089378,0.0005332074,0.04422931,0.1554245,0.01159467,0.02484297,0.7592731],"study_design_scores_gemma":[0.0002149812,0.0005604277,0.00277323,0.00005127771,0.0002961039,0.001654781,0.0002226402,0.8270909,0.1116137,0.01378705,0.04159376,0.0001410677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0450961,0.0006698886,0.9238119,0.0002134649,0.0001780337,0.0002853916,0.001012036,0.01939915,0.009334133],"genre_scores_gemma":[0.2405009,0.0003699783,0.7486199,0.0002003945,0.0001402376,0.0002768523,0.003903338,0.0005296355,0.005458911],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004705294,"threshold_uncertainty_score":0.01574075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02987048605879337,"score_gpt":0.2730560117679839,"score_spread":0.2431855257091905,"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."}}