This paper presents the results of the WMT17 Metrics Shared Task. We asked participants of this task to score the outputs of the MT systems involved in the WMT17 news translation task and Neural MT training task. We collected scores of 14 metrics from 8 research groups. In addition to that, we computed scores of 7 standard metrics (BLEU, SentBLEU, NIST, WER, PER, TER and CDER) as baselines. The collected scores were evaluated in terms of system-level correlation (how well each metric's scores correlate with WMT17 official manual ranking of systems) and in terms of segment level correlation (how often a metric agrees with humans in judging the quality of a particular sentence).This year, we build upon two types of manual judgements: direct assessment (DA) and HUME manual semantic judgements.
This paper presents the results of the WMT13 Metrics Shared Task. We asked participants of this task to score the outputs of the MT systems involved in WMT13 Shared Translation Task. We collected scores of 16 metrics from 8 research groups. In addition to that we computed scores of 5 standard metrics such as BLEU, WER, PER as baselines. Collected scores were evaluated in terms of system level correlation (how well each metric's scores correlate with WMT13 official human scores) and in terms of segment level correlation (how often a metric agrees with humans in comparing two translations of a particular sentence).
We report on methods to create the largest publicly available parallel corpora by crawling the web, using open source software. We empirically compare alternative methods and publish benchmark data sets for sentence alignment and sentence pair filtering. We also describe the parallel corpora released and evaluate their quality and their usefulness to create machine translation systems.
This paper presents the results of the WMT13 Metrics Shared Task. We asked participants of this task to score the outputs of the MT systems involved in WMT13 Shared Translation Task. We collected scores of 16 metrics from 8 research groups. In addition to that we computed scores of 5 standard metrics such as BLEU, WER, PER as baselines. Collected scores were evaluated in terms of system level correlation (how well each metric's scores correlate with WMT13 official human scores) and in terms of segment level correlation (how often a metric agrees with humans in comparing two translations of a particular sentence).
Background: Although heart failure (HF) is a common cause of hospital admissions, few data describe temporal trends in HF hospitalization. We present data on number of HF admissions, length of stay (LOS), and inpatient mortality in the United States, 1996-2009. Hypothesis:To assess HF hospitalizations in a national sample of United States population.Methods: Data were obtained from the National Hospital Discharge Survey (NHDS), a national probability sample survey of discharges conducted annually by the National Center for Health Statistics. Sampling weights are applied to raw NHDS data to produce national estimates. Hospitalizations with a primary diagnosis of HF were identified using ICD-9-CM codes. We excluded hospitalizations where HF was a secondary diagnosis. Weighted least squares regression was used to test for linear trends in HF hospitalizations. Conclusions:In a nationally representative sample of HF hospitalizations, mean LOS and inpatient mortality rates declined over the past 2 decades. HF management cost is most likely to be reduced by decreasing the number of HF admissions.
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