1,721,009 research outputs found
Report on the Eighth International Conference on Computational Creativity
Full text linkThe Eighth International Conference on Computational Creativity (ICCC’17)1 was hosted at the Georgia Institute of Technology in Atlanta, Georgia, USA from June 19th - June 23rd, 2017. The ICCC’17 organising committee consisted of Ashok Goel (General Chair), Kazjon Grace (Workshop Co-chair), Matthew Guzdial (Media Chair), Mikhail Jacob (Local Chair), Anna Jordanous (Program Co-chair), Ruli Manurung (Workshop Co-chair) and Alison Pease (Program Co-chair). This report summarises the main topics addressed
What makes a musical improvisation creative?
Full text linkBackground in musical improvisation and creativity. What makes musical improvisation
creative? And what exactly is it that justifies one improviser being described as more creative
than another? For a clearer understanding, it is a practical necessity to use an approach such as
those of Berliner (1994) and Gibbs (2010), who make the study of improvisational creativity
more tangible by identifying key constituent parts, rather than treat creativity as ineffable
(Bailey 1993).
Background in computational linguistics. The log likelihood ratio statistic can be used to
compare two sets of texts (corpora) to examine word distribution patterns (Rayson & Garside
2000, Dunning 1993). Using this statistic, words are identified which are associated with
academic papers on creativity. Lin’s similarity measure (Lin 1998) is then used as a basis for
clustering words with similar meanings using the algorithm Chinese Whispers (Biemann 2006).
Analysis of the clusters reveals fourteen key components of creativity.
Aims. To model creativity in musical improvisation by identifying components of creativity
using computational linguistics techniques and understanding how each contributes to
creativity in improvisation.
Main contribution. The paper presents an empirical, language-based approach to
understanding creativity in musical improvisation. This approach is based upon treating
creativity as having common features that transcend different types of creativity but that vary in
importance depending on the type of creativity. Fourteen key components of creativity are
identified from an analysis of a corpus of texts on creativity. A study is then conducted to
investigate the relative importance of each of these components in musical improvisational. All
fourteen components are considered relevant to some degree, but particular significance is
attached to three of them: the ability to communicate and interact, the possession of relevant
musical knowledge and skills, and emotional engagement and intention. It is notable that the
products of improvisation are relatively less important than these process-based aspects.
Implications. The work provides a model of musical improvisational creativity as a set of
guidelines or benchmarks for evaluating how creative a musical improviser is. Such a detailed
understanding helps improvisers identify what areas to work on in order to develop their
creativity (Gibbs 2010)
Waiting... with Rachel and Peter: Podcast funded by Arts Council England/Wellcome Trust
No full textFuel, Roundhouse and King’s Cultural Institute present
Waiting… with Rachel and Peter
By Stefan Kaegi in collaboration with Anna Jordanous and Niki Neecke. Voices by Acapela Group.
Waiting… with Rachel and Peter is the fourth in our new series of podcasts called While You Wait, each of which is a different meditation on the idea of waiting and created by artists in collaboration with academics from King's College London.
Waiting… with Rachel and Peter has been made by Berlin based artist Stefan Kaegi in collaboration with Anna Jordanous, Research Associate, Centre for e-Research and sound designer Niki Neecke.
While You Wait is funded by Arts Council England and a Wellcome Trust Arts Award.
An accompanying video interview featuring Stefan Kaegi and Anna Jordanous is available at https://www.youtube.com/watch?v=GcG43H_jMN
Investigating the role of score following in automatic musical accompaniment
Get PDFWhen suitable accompanists are not available to a soloist musician, an alternative possibility is to use computer-generated accompaniment. A computer accompanist should interact with the soloist and adapt to the soloist's playing as a human accompanist would, both reacting to expressive nuances of tempo and to unintentional errors such as wrong or mistimed notes. Over the past 25 years, accompaniment systems have been developed, all of which employ some form of score following: the process of following a musician's progress through the score of a piece during performance. This work considers the role of score following in automatic accompaniment. In this investigation we developed a computer accompanist that employs score following. Our computer musician uses Hidden Markov Models to model the score by metrical structure and to provide accompaniment to a soloist playing monophonic music in real time, as the soloist is playing. Working with MIDI input/output, it tracks tempo fluctuations, anticipates the soloist's next note and supports some amount of unintentional deviation from the score. Qualitative evaluation, by human testers, and quantitative evaluation, using measurable criteria taken from MIREX, reported that the system performs adequately. We then used interviews with eight human accompanists to consider how well a score following system models the accompaniment process. This evaluation raises questions about the musical interaction between soloist and accompanist that have received relatively little attention. The information we gathered from interviews suggests the importance of other aspects of accompaniment, such as the sharing of shape of the performance between musicians, rather than treating the accompanist as purely subservient. We discuss the implications of these issues for the design of automated accompanists
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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