Concept Blending and Dissimilarity: Factors for Creative Design Process: A Comparison between the Linguistic Interpretation Process and Design Process

This study investigated the design process in order to clarify the characteristics of the essence of the creative design process vis-à-vis the interpretation process, by carrying out design experiments. The authors analyzed the characteristics of the creative design process by comparing it with the linguistic interpretation process, from the viewpoints of thought types (analogy, blending, and thematic relation) and recognition types (commonalities and alignable and nonalignable differences). A new concept can be created by using the noun-noun phrase as the process of synthesizing two concepts—the simplest and most essential process in formulating a new concept from existing ones. Furthermore, the noun-noun phrase can be interpreted in a natural way. In our experiment, the subjects were required to interpret a novel noun-noun phrase, create a design concept from the same noun-noun phrase, and list the similarities and dissimilarities between the two nouns. The authors compare the results of the thought types and recognition types, focusing on the perspective of the manner in which things were viewed, i.e., in terms of similarities and dissimilarities. A comparison of the results reveals that blending and nonalignable differences characterize the creative design process. The findings of this research will contribute a framework of design practice, to enhance both students’ and designers’ creativity for concept formation in design, which relates to the development of innovative design. Keywords: Noun-Noun phrase; Design; Creativity; Blending; Nonalignable difference</p

Musemo: Express Musical Emotion Based on Neural Network

Department of Urban and Environmental Engineering (Convergence of Science and Arts)Music elicits emotional responses, which enable people to empathize with the emotional states induced by music, experience changes in their current feelings, receive comfort, and relieve stress (Juslin & Laukka, 2004). Music emotion recognition (MER) is a field of research that extracts emotions from music through various systems and methods. Interest in this field is increasing as researchers try to use it for psychiatric purposes. In order to extract emotions from music, MER requires music and emotion labels for each music. Many MER studies use emotion labels created by non-music-specific psychologists such as Russell???s circumplex model of affects (Russell, 1980) and Ekman???s six basic emotions (Ekman, 1999). However, Zentner, Grandjean, and Scherer suggest that emotions commonly used in music are subdivided into specific areas, rather than spread across the entire spectrum of emotions (Zentner, Grandjean, & Scherer, 2008). Thus, existing MER studies have difficulties with the emotion labels that are not widely agreed through musicians and listeners. This study proposes a musical emotion recognition model ???Musemo??? that follows the Geneva emotion music scale proposed by music psychologists based on a convolution neural network. We evaluate the accuracy of the model by varying the length of music samples used as input of Musemo and achieved RMSE (root mean squared error) performance of up to 14.91%. Also, we examine the correlation among emotion labels by reducing the Musemo???s emotion output vector to two dimensions through principal component analysis. Consequently, we can get results that are similar to the study that Vuoskoski and Eerola analyzed for the Geneva emotion music scale (Vuoskoski & Eerola, 2011). We hope that this study could be expanded to inform treatments to comfort those in need of psychological empathy in modern society.clos

Analyzing Visual Mappings of Traditional and Alternative Music Notation

In this paper, we postulate that combining the domains of information visualization and music studies paves the ground for a more structured analysis of the design space of music notation, enabling the creation of alternative music notations that are tailored to different users and their tasks. Hence, we discuss the instantiation of a design and visualization pipeline for music notation that follows a structured approach, based on the fundamental concepts of information and data visualization. This enables practitioners and researchers of digital humanities and information visualization, alike, to conceptualize, create, and analyze novel music notation methods. Based on the analysis of relevant stakeholders and their usage of music notation as a mean of communication, we identify a set of relevant features typically encoded in different annotations and encodings, as used by interpreters, performers, and readers of music. We analyze the visual mappings of musical dimensions for varying notation methods to highlight gaps and frequent usages of encodings, visual channels, and Gestalt laws. This detailed analysis leads us to the conclusion that such an under-researched area in information visualization holds the potential for fundamental research. This paper discusses possible research opportunities, open challenges, and arguments that can be pursued in the process of analyzing, improving, or rethinking existing music notation systems and techniques.Comment: 5 pages including references, 3rd Workshop on Visualization for the Digital Humanities, Vis4DH, IEEE Vis 201

Interactive Spaces. Models and Algorithms for Reality-based Music Applications

Reality-based interfaces have the property of linking the user's physical space with the computer digital content, bringing in intuition, plasticity and expressiveness. Moreover, applications designed upon motion and gesture tracking technologies involve a lot of psychological features, like space cognition and implicit knowledge. All these elements are the background of three presented music applications, employing the characteristics of three different interactive spaces: a user centered three dimensional space, a floor bi-dimensional camera space, and a small sensor centered three dimensional space. The basic idea is to deploy the application's spatial properties in order to convey some musical knowledge, allowing the users to act inside the designed space and to learn through it in an enactive way