Computational Creativity and Music Generation Systems: An Introduction to the State of the Art

Computational Creativity is a multidisciplinary field that tries to obtain creative behaviors from computers. One of its most prolific subfields is that of Music Generation (also called Algorithmic Composition or Musical Metacreation), that uses computational means to compose music. Due to the multidisciplinary nature of this research field, it is sometimes hard to define precise goals and to keep track of what problems can be considered solved by state-of-the-art systems and what instead needs further developments. With this survey, we try to give a complete introduction to those who wish to explore Computational Creativity and Music Generation. To do so, we first give a picture of the research on the definition and the evaluation of creativity, both human and computational, needed to understand how computational means can be used to obtain creative behaviors and its importance within Artificial Intelligence studies. We then review the state of the art of Music Generation Systems, by citing examples for all the main approaches to music generation, and by listing the open challenges that were identified by previous reviews on the subject. For each of these challenges, we cite works that have proposed solutions, describing what still needs to be done and some possible directions for further research

Evaluating computational creativity: a standardised procedure for evaluating creative systems and its application

This thesis proposes SPECS: a Standardised Procedure for Evaluating Creative Systems. No methodology has been accepted as standard for evaluating the creativity of a system in the field of computational creativity and the multi-faceted and subjective nature of creativity generates substantial definitional issues. Evaluative practice has developed a general lack of rigour and systematicity, hindering research progress. SPECS is a standardised and systematic methodology for evaluating computational creativity. It is flexible enough to be applied to a variety of different types of creative system and adaptable to specific demands in different types of creativity. In the three-stage process of evaluation, researchers are required to be specific about what creativity entails in the domain they work in and what standards they test a system’s creativity by. To assist researchers, definitional issues are investigated and a set of components representing aspects of creativity is presented, which was empirically derived using computational linguistics analysis. These components are recommended for use within SPECS, being offered as a general definition of creativity that can be customised to account for any specific priorities for creativity in a given domain. SPECS is applied in a case study for detailed comparisons of the creativity of three musical improvisation systems, identifying which systems are more creative than others and why. In a second case study, SPECS is used to capture initial impressions on the creativity of systems presented at a 2011 computational creativity research event. Five systems performing different creative tasks are compared and contrasted. These case studies exemplify the valuable information that can be obtained on a system’s strengths and weaknesses. SPECS gives researchers vital feedback for improving their systems’ creativity, informing further progress in computational creativity research

Flexibility and usability: Focal point of graduate students’ knowledge level of the features of SAKAI learning management system

Coupled with the global pandemic (COVID-19) and technological advancement, the SAKAI learning management system (LMS) was initiated to deliver synchronous, asynchronous, blended instruction to break the artificial boundaries towards delivering quality education. This requires students to acquire the requisite knowledge to develop self-regulated skills to navigate through inbuilt features of SAKAI LMS to ensure usability, flexibility, and accessibility. To ascertain the usability, flexibility and accessibility of the SAKAI LMS, this study sought to examine the knowledge level of graduate students on the features of SAKAI LMS. The cross-sectional survey design was used to gather data. Using the SAKAI LMS, the systematic sampling technique was used to sample 209 students drawn from the six (6) schools within the three colleges of the University of Ghana. A close-ended questionnaire on a three-point Likert Scale was employed to elicit information on respondents’ knowledge of the features of the SAKAI LMS. The study’s findings revealed that the respondents possessed a low level of knowledge on forum tools, lesson tools, quizzes and assessment tools, resources tools as well as chatroom tools of the SAKAI LMS. However, there was a significant difference between the level of knowledge of the features of SAKAI LMS across genders, but there was no statistically significant difference in the level of knowledge of the SAKAI LMS across the age and college of affiliation of respondents. Based on the study’s findings, university management needs to organise some SAKAI LMS training and orientation for at least three days to enable students to acquire the requisite knowledge and understanding of the different inbuilt features of the SAKAI LMS. Through this exercise, respondents will build and develop self-regulatory skills. This is because the SAKAI LMS can become beneficial if respondents possess the mastery of knowledge to control and monitor their traits of metacognition as they engage with the SAKAI LMS

Evaluating computational creativity: a standardised procedure for evaluating creative systems and its application

This thesis proposes SPECS: a Standardised Procedure for Evaluating Creative Systems. No methodology has been accepted as standard for evaluating the creativity of a system in the field of computational creativity and the multi-faceted and subjective nature of creativity generates substantial definitional issues. Evaluative practice has developed a general lack of rigour and systematicity, hindering research progress. SPECS is a standardised and systematic methodology for evaluating computational creativity. It is flexible enough to be applied to a variety of different types of creative system and adaptable to specific demands in different types of creativity. In the three-stage process of evaluation, researchers are required to be specific about what creativity entails in the domain they work in and what standards they test a system’s creativity by. To assist researchers, definitional issues are investigated and a set of components representing aspects of creativity is presented, which was empirically derived using computational linguistics analysis. These components are recommended for use within SPECS, being offered as a general definition of creativity that can be customised to account for any specific priorities for creativity in a given domain. SPECS is applied in a case study for detailed comparisons of the creativity of three musical improvisation systems, identifying which systems are more creative than others and why. In a second case study, SPECS is used to capture initial impressions on the creativity of systems presented at a 2011 computational creativity research event. Five systems performing different creative tasks are compared and contrasted. These case studies exemplify the valuable information that can be obtained on a system’s strengths and weaknesses. SPECS gives researchers vital feedback for improving their systems’ creativity, informing further progress in computational creativity research

Adaptive Search and Constraint Optimisation in Engineering Design

The dissertation presents the investigation and development of novel adaptive computational techniques that provide a high level of performance when searching complex high-dimensional design spaces characterised by heavy non-linear constraint requirements. The objective is to develop a set of adaptive search engines that will allow the successful negotiation of such spaces to provide the design engineer with feasible high performance solutions. Constraint optimisation currently presents a major problem to the engineering designer and many attempts to utilise adaptive search techniques whilst overcoming these problems are in evidence. The most widely used method (which is also the most general) is to incorporate the constraints in the objective function and then use methods for unconstrained search. The engineer must develop and adjust an appropriate penalty function. There is no general solution to this problem neither in classical numerical optimisation nor in evolutionary computation. Some recent theoretical evidence suggests that the problem can only be solved by incorporating a priori knowledge into the search engine. Therefore, it becomes obvious that there is a need to classify constrained optimisation problems according to the degree of available or utilised knowledge and to develop search techniques applicable at each stage. The contribution of this thesis is to provide such a view of constrained optimisation, starting from problems that handle the constraints on the representation level, going through problems that have explicitly defined constraints (i.e., an easily computed closed form like a solvable equation), and ending with heavily constrained problems with implicitly defined constraints (incorporated into a single simulation model). At each stage we develop applicable adaptive search techniques that optimally exploit the degree of available a priori knowledge thus providing excellent quality of results and high performance. The proposed techniques are tested using both well known test beds and real world engineering design problems provided by industry.British Aerospace, Rolls Royce and Associate