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.

Intelligent Assembly Time Analysis Using a Digital Knowledge-Based Approach

The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for intelligent time analysis of aircraft assembly processes within a digital manufacturing framework. A knowledge system is developed so that the design knowledge can be intelligently retrieved for implementing assembly time analysis automatically. A time estimation method based on MOST, is reviewed and employed. Knowledge capture, transfer and storage within the digital manufacturing environment are extensively discussed. Configured plantypes, GUIs and functional modules are designed and developed for the automated time analysis. An exemplar study using an aircraft panel assembly from a regional jet is also presented. Although the method currently focuses on aircraft assembly, it can also be well utilized in other industry sectors, such as transportation, automobile and shipbuilding. The main contribution of the work is to present a methodology that facilitates the integration of time analysis with design and manufacturing using a digital manufacturing platform solution.

Safeguarding: A case for intelligent risk management

‘Risk’ in social work is typically read as risk-of-bads, and specifically extreme bads. This paper develops the implications of the logical objection to attempts to predict low frequency extreme events (such as child homicides). Our argument is that if we focus on these low probability high cost outcomes—these heart wrenching, but unpredictable, tragedies—we take social work away from the good that it can do, leave it open to inappropriate disapprobation, and, in terms of outcomes, do less well by the vulnerable. This point is reinforced by discussion of developments in other academic fields, and by further examination of the logic (and the morality) of protection under uncertainty. We explore the implications for the way social work should be evaluated. A proper academic understanding of risk, and decision making under uncertainty, has, we argue clear practical implications.