Thesis (S.M.)-Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2007. In order to have as diverse a range of applications as possible, care was taken to avoid tying jMIR to any particular types of music classification. jMIR permits users to extract meaningful information from audio recordings, symbolic musical representations and cultural information available on the Internet to use machine learning technologies to automatically build classification models to automatically collect profiling statistics and detect metadata errors in musical collections to perform experiments on large, stylistically diverse and well-labelled collections of music in both audio and symbolic formats and to store and distribute information that is essential to automatic music classification in expressive and flexible standardised file formats.
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This dissertation focuses on the development of jMIR, a suite of powerful, flexible, accessible and original software tools that can be used to design, share and apply a wide range of automatic music classification technologies.
(54 ref)Īutomatic music classification is a wide-ranging and multidisciplinary area of inquiry that offers significant benefits from both academic and commercial perspectives. In turn, an emotion's goodness of example (prototypicality) ranking predicted how readily it comes to mind when one is asked to list emotions, how likely it is to be labeled as an emotion when one is asked what sort of thing it is, how readily it can be substituted for the word emotion in sentences without their sounding unnatural, and the degree to which it resembles other emotion categories in terms of shared features. As hypothesized, the concept of emotion was found to have an internal structure: Happiness, love, anger, fear, awe, respect, envy, and other types of emotion could be reliably ordered from better to poorer examples of emotion. Undergraduates served as Ss in all experiments. Specifically it is argued that membership in the concept of emotion is a matter of degree rather than all-or-none (that the concept has an internal structure) and that no sharp boundary separates members from nonmembers (that the concept has fuzzy boundaries). Reports 7 studies that explored the possibility that the concept of emotion is better understood from a prototype perspective than from a classical one. (27 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved) Dominance and submissiveness factors were also included in the study, but invalidity of the scales used precluded any conclusions regarding their bipolarity.
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Thayer's (1970) 4 factors of activation plus a measure of depression. In turn, pleasure–displeasure and degree of arousal formed a 2-dimensional bipolar space that accounted for almost all of the reliable variance in R. When these biases were taken into account, pleasure was the bipolar opposite of displeasure and arousal of sleepiness. The present study of 150 undergraduates' self-report data on 11 affect scales showed that response format and acquiescence response style significantly shifted correlations between hypothesized opposites away from showing bipolarity. Numerous previous studies found monopolar rather than bipolar dimensions of affect (defined as emotion represented in language), but they may have included methodological biases against bipolarity. (70 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved) Ross's (1938) technique for a circular ordering of variables, a multidimensional scaling procedure based on perceived similarity among the terms, a unidimensional scaling on hypothesized pleasure–displeasure and degree-of-arousal dimensions, and a principal-components analysis of 343 Ss' self-reports of their current affective states. Supportive evidence was obtained by scaling 28 emotion-denoting adjectives in 4 different ways: R.
This model was offered both as a way psychologists can represent the structure of affective experience, as assessed through self-report, and as a representation of the cognitive structure that laymen utilize in conceptualizing affect. The evidence suggests that these interrelationships can be represented by a spatial model in which affective concepts fall in a circle in the following order: pleasure (0), excitement (45), arousal (90), distress (135), displeasure (180), depression (225), sleepiness (270), and relaxation (315).
However, there is other evidence that rather than being independent, these affective dimensions are interrelated in a highly systematic fashion. Factor-analytic evidence has led most psychologists to describe affect as a set of dimensions, such as displeasure, distress, depression, excitement, and so on, with each dimension varying independently of the others.
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