Plenary Speakers

 

     
Cognitive Models of Music Perception
Rie Matsunaga
Department of Human Sciences, Kanagawa University, Japan

Abstract

Most people associate music with emotional and aesthetic awareness. The emotional awareness of music is not independent from understanding of musical structure. In other words, music perception, at least in part, underlies the emotional awareness of music. In this talk, I will discuss cognitive models of music perception.
As with language, infants are born culture-free with respect to music perception although they may have some innate constraints. As the growing-up process proceeds, listeners’ music perception is largely governed by their musical experiences and learning, or in psychological terms the ‘musical schema’ that reflects implicit knowledge acquired through long-term and everyday exposure to music of their own culture. Thus, when proposing a cognitive model, it should reflect culture-general properties only at a structure level while allowing for flexibility in acquiring and changing internal representations (which correspond to a concept of musical schemas) as a function of music exposure. One important issue is how to represent individual differences of musical schemas in a coherent way while keeping the fixed structure model.
In this talk, after overviewing how listeners perceive a sequence of tones as ‘music’ in their mind, I will focus on a perceptual process of pitch structure or ‘tonality’ perception. Subsequently, I will introduce several behavioral and neuroimaging studies that investigated differences and similarities in tonality perception between listeners of different ages and different music cultures who were at various levels of musical training. Based on evidence of these studies, I will describe fundamental characteristics of cognitive models of tonality perception.

Biography

Rie Matsunaga obtained Ph. D. degree in Cognitive Psychology from Hokkaido University in 2005. Since April 2017, she is currently an Associate professor of Department Human Sciences, at Kanagawa University. Prof. Matsunaga' s research goal is to understand how mechanisms underlying perception of music arise and change from infancy through adulthood as an experience in one's culture and cognitive (or universal) development processes.


 

     
Self-aware Computing Systems: From Psychology to Engineering
Peter Lewis
ALICE, Aston University, UK

Abstract

There are a number of fundamental changes in the way computing systems are being developed, deployed and used. They are becoming increasingly large, heterogeneous, uncertain, dynamic and decentralised. These complexities lead to behaviours during run time that are difficult to understand, predict, and control. One vision for how to rise to this challenge is to endow computing systems with increased self-awareness, in order to enable more advanced autonomous adaptive behaviour. A desire for self-awareness has arisen in a variety of areas of computer science and engineering over the last two decades.
In this context, we have developed a conceptual framework that provides researchers with a common language with which to describe the self-awareness capabilities of their systems. Our framework is based on a developing fundamental understanding of what self-awareness concepts might mean for the design and operation of computing systems, drawing on self-awareness theories from psychology and other related fields.
I will show how explicit consideration of these concepts may be beneficial in the engineering of adaptive computing systems, that are better able to manage trade-offs between conflicting goals in a complex environment at run time, while reducing the need for a priori domain modelling at design or deployment time.
I will discuss how computational self-awareness may include knowledge of internal state, history, social or physical environment, goals, and further, even a system's own way of representing and reasoning about these things.
Finally, I will describe some of our work in some example application domains: distributed smart-camera networks, volunteer cloud computing, and mobile robotics, where self-awareness can increase runtime adaptivity and robustness, and avoid the need for a priori information at design-time.

Biography

Dr. Peter Lewis is a Senior Lecturer in Computer Science at Aston University, in Birmingham. With a background in computational intelligence, Peter has made significant contribution to the field of self-aware computing, including the foundational book Self-aware Computing Systems: An Engineering Approach, in 2016. More broadly, his research is often inspired by biological, social and psychological processes, and advances our understanding about how to build complex computing systems that learn and adapt on an ongoing basis. Through ongoing industrial research collaborations, his work has been applied in areas such as smart camera networks, interactive music devices, avionics, manufacturing, and cloud computing. He obtained his PhD at the University of Birmingham, and is a member of the Aston Lab for Intelligent Collectives Engineering (ALICE).