Lisa P. Mason

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We discuss two NIST coordinated evaluations of automatic language recognition technology planned for calendar year 2015 along with possible additional plans for the future. The first is the Language Recognition i-Vector Machine Learning Challenge, largely modeled on the 2013-2014 Speaker Recognition i-Vector Machine Learning Challenge. This online(More)
In 2015 NIST coordinated the first language recognition evaluation (LRE) that used i-vectors as input, with the goals of attracting researchers outside of the speech processing community to tackle the language recognition problem, exploring new ideas in machine learning for use in language recognition, and improving recognition accuracy. The Language(More)
Thirty-day heart failure readmissions can be reduced if multiple interventions, such as 7-day postdischarge follow-up, are implemented, but this task is challenging for health systems. Ten hospitals participated in a multisystem collaborative implementing evidence-based strategies. The overall 30-day readmission rate was reduced more in the collaborating(More)
In late 2013 and 2014, the National Institute of Standards and Technology (NIST) coordinated an i-vector challenge utilizing data from previous NIST Speaker Recognition Evaluations. Following the evaluation period, a second phase of the challenge was held, where speaker labels were made available for system development. The second phase included system(More)
In 2015, NIST conducted the most recent in an ongoing series of Language Recognition Evaluations (LRE) meant to foster research in language recognition. The 2015 Language Recognition Evaluation featured 20 target languages grouped into 6 language clusters. The evaluation was focused on distinguishing languages within each cluster, without disclosing which(More)
5054 Background: Currently, early detection of prostate cancer relies primarily on an abnormal digital rectal examination (DRE) and an elevated prostate-specific antigen (PSA) level leading to a prostate biopsy. However, because of low positive predictive values, up to 75% of men with elevated PSA and/or suspicious DRE have a negative biopsy. We(More)
In 2016, the National Institute of Standards and Technology (NIST) conducted the most recent in an ongoing series of speaker recognition evaluations (SRE) to foster research in robust text-independent speaker recognition, as well as measure performance of current state-of-the-art systems. Compared to previous NIST SREs, SRE16 introduced several new aspects(More)
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