Towards an intelligent score following system: Handling of mistakes and jumps encountered during piano practicing

Score following has been an important area of research in AI and music since the mid 80's. Various systems were developed, but they were predominantly for providing automated accompaniment to live concert performances, dealing mostly with issues relating to pitch detection and identification of embellished melodies. They have a big potential in the area of education where student performers benefit in practice situations. Current accompaniment systems are not designed to deal with errors that may occur during practising. In this paper we present a system developed to provide accompaniment for students practising at home. First a survey of score following will be given. Then the capabilities of the system will be explained, and the results from the first experiments of the monophonic score following system will be presented.

Cardiovascular disease risk profiles among 'healthy' siblings of patients with early-onset cardiovascular disease:Application of the new SCORE system

BACKGROUND: Cardiovascular disease (CVD) occurs more frequently in individuals with a family history of premature CVD. Within families the demographics of CVD are poorly described. DESIGN: We examined the risk estimation based on the Systematic Coronary Risk Evaluation (SCORE) system and the Joint British Guidelines (JBG) for older unaffected siblings of patients with premature CVD (onset ≤55 years for men and ≤60 years for women). METHODS: Between August 1999 and November 2003 laboratory and demographic details were collected on probands with early-onset CVD and their older unaffected siblings. Siblings were screened for clinically overt CVD by a standard questionnaire and 12-lead electrocardiogram (ECG). RESULTS: A total of 790 siblings was identified and full demographic details were available for 645. The following siblings were excluded: 41 with known diabetes mellitus; seven with random plasma glucose of 11.1 mmol/l or greater; and eight with ischaemic ECG. Data were analysed for 589 siblings from 405 families. The mean age was 55.0 years, 43.1% were men and 28.7% were smokers. The mean total serum cholesterol was 5.8 mmol/l and hypertension was present in 49.4%. Using the SCORE system, when projected to age 60 years, 181 men (71.3%) and 67 women (20.0%) would be eligible for risk factor modification. Using JBG with a 10-year risk of 20% or greater, 42 men (16.5%) and four women (1.2%) would be targeted. CONCLUSIONS: Large numbers of these asymptomatic individuals meet both European and British guidelines for the primary prevention of CVD and should be targeted for risk factor modification. The prevalence of individuals defined as eligible for treatment is much higher when using the SCORE system. © 2007 European Society of Cardiology.

School Neighborhood Disadvantage as a Predictor of Long-Term Sick Leave Among Teachers: Prospective Cohort Study

This ongoing prospective study examined characteristics of school neighborhood and neighborhood of residence as predictors of sick leave among school teachers. School neighborhood income data for 226 lower-level comprehensive schools in 10 towns in Finland were derived from Statistics Finland and were linked to register-based data on 3,063 teachers with no long-term sick leave at study entry. Outcome was medically certified (> 9 days) sick leave spells during a mean follow-up of 4.3 years from data collection in 2000-2001. A multilevel, cross-classified Poisson regression model, adjusted for age, type of teaching job, length and type of job contract, school size, baseline health status, and income level of the teacher's residential area, showed a rate ratio of 1.30 (95% confidence interval: 1.03, 1.63) for sick leave among female teachers working in schools located in low-income neighborhoods compared with those working in high-income neighborhoods. A low income level of the teacher's residential area was also independently associated with sick leave among female teachers (rate ratio = 1.50, 95% confidence interval: 1.18, 1.91). Exposure to both low-income school neighborhoods and low-income residential neighborhoods was associated with the greatest risk of sick leave (rate ratio = 1.71, 95% confidence interval: 1.27, 2.30). This study indicates that working and living in a socioeconomically disadvantaged neighborhood is associated with increased risk of sick leave among female teachers.