346 resultados para Music genre classification
Resumo:
This paper considers issues of methodological innovation in communication, media and cultural studies, that arise out of the extent to which we now live in a media environment characterised by an digital media abundance, the convergence of media platforms, content and services, and the globalisation of media content through ubiquitous computing and high-speed broadband networks. These developments have also entailed a shift in the producer-consumer relationships that characterised the 20th century mass communications paradigm, with the rapid proliferation of user-created content, accelerated innovation, the growing empowerment of media users themselves, and the blurring of distinctions between public and private, as well as age-based distinctions in terms of what media can be accessed by whom and for what purpose. It considers these issues through a case study of the Australian Law Reform Commission's National Classification Scheme Review.
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From one view of composition—let us call it the inspired or “Mozartian” view—musical compositions arrive fully formed in the mind of the composer and simply require transcription. In reality, however, it seems that very few people are so inspired, and composition is often more akin to a gradual clarification and refinement of partially formed ideas on the musical landscape. Particular landmarks in the compositional landscape tend to become clear before others, such that the incomplete piece is a patchwork of disconnected musical islands. An interactive evolutionary morphing system may provide some assistance for composers, to help build bridges between musical islands by generating hybrid musical transitions.
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Musical value cannot be experienced without direct knowledge of music, and engagement with the interactive elements of materials, expressive character and structure. Through these channels something is communicated, something is transmitted, some residue of ‘meaning’ is left with us. When a work of art stirs us it is more than simply sensory stimulation or some kind of emotional indulgence. We are gaining knowledge and expanding our experience... contributing to knowledge of ourselves and of the world.
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In this article I would like to examine the promise and possibilities of music, digital media and National Broadband Network. I will do this based on concepts that have emerged from a study undertaken by Professor Andrew Brown and I that categorise technologies into what we term representational technologies and technologies with agency
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Purpose – The work presented in this paper aims to provide an approach to classifying web logs by personal properties of users. Design/methodology/approach – The authors describe an iterative system that begins with a small set of manually labeled terms, which are used to label queries from the log. A set of background knowledge related to these labeled queries is acquired by combining web search results on these queries. This background set is used to obtain many terms that are related to the classification task. The system then ranks each of the related terms, choosing those that most fit the personal properties of the users. These terms are then used to begin the next iteration. Findings – The authors identify the difficulties of classifying web logs, by approaching this problem from a machine learning perspective. By applying the approach developed, the authors are able to show that many queries in a large query log can be classified. Research limitations/implications – Testing results in this type of classification work is difficult, as the true personal properties of web users are unknown. Evaluation of the classification results in terms of the comparison of classified queries to well known age-related sites is a direction that is currently being exploring. Practical implications – This research is background work that can be incorporated in search engines or other web-based applications, to help marketing companies and advertisers. Originality/value – This research enhances the current state of knowledge in short-text classification and query log learning. Classification schemes, Computer networks, Information retrieval, Man-machine systems, User interfaces
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This study aimed to examine the effects on driving, usability and subjective workload of performing music selection tasks using a touch screen interface. Additionally, to explore whether the provision of visual and/or auditory feedback offers any performance and usability benefits. Thirty participants performed music selection tasks with a touch screen interface while driving. The interface provided four forms of feedback: no feedback, auditory feedback, visual feedback, and a combination of auditory and visual feedback. Performance on the music selection tasks significantly increased subjective workload and degraded performance on a range of driving measures including lane keeping variation and number of lane excursions. The provision of any form of feedback on the touch screen interface did not significantly affect driving performance, usability or subjective workload, but was preferred by users over no feedback. Overall, the results suggest that touch screens may not be a suitable input device for navigating scrollable lists.
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A broad range of positions is articulated in the academic literature around the relationship between recordings and live performance. Auslander (2008) argues that “live performance ceased long ago to be the primary experience of popular music, with the result that most live performances of popular music now seek to replicate the music on the recording”. Elliott (1995) suggests that “hit songs are often conceived and produced as unambiguous and meticulously recorded performances that their originators often duplicate exactly in live performances”. Wurtzler (1992) argues that “as socially and historically produced, the categories of the live and the recorded are defined in a mutually exclusive relationship, in that the notion of the live is premised on the absence of recording and the defining fact of the recorded is the absence of the live”. Yet many artists perform in ways that fundamentally challenge such positions. Whilst it is common practice for musicians across many musical genres to compose and construct their musical works in the studio such that the recording is, in Auslander’s words, the ‘original performance’, the live version is not simply an attempt to replicate the recorded version. Indeed in some cases, such replication is impossible. There are well known historical examples. Queen, for example, never performed the a cappella sections of Bohemian Rhapsody because it they were too complex to perform live. A 1966 recording of the Beach Boys studio creation Good Vibrations shows them struggling through the song prior to its release. This paper argues that as technology develops, the lines between the recording studio and live performance change and become more blurred. New models for performance emerge. In a 2010 live performance given by Grammy Award winning artist Imogen Heap in New York, the artist undertakes a live, improvised construction of a piece as a performative act. She invites the audience to choose the key for the track and proceeds to layer up the various parts in front of the audience as a live performance act. Her recording process is thus revealed on stage in real time and she performs a process that what would have once been confined to the recording studio. So how do artists bring studio production processes into the live context? What aspects of studio production are now performable and what consistent models can be identified amongst the various approaches now seen? This paper will present an overview of approaches to performative realisations of studio produced tracks and will illuminate some emerging relationships between recorded music and performance across a range of contexts.
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This paper examines the integration of computing technologies into music education research in a way informed by constructivism. In particular, this paper focuses on an approach established by Jeanne Bamberger, which the author also employs, that integrates software design, pedagogical exploration, and the building of music education theory. In this tradition, researchers design software and associated activities to facilitate the interactive manipulation of musical structures and ideas. In short, this approach focuses on designing experiences and tools that support musical thinking and doing. In comparing the work of Jean Bamberger with that of the author, this paper highlights and discusses issues of significance and identifies lessons for future research.
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In this paper, we describe the main processes and operations in mining industries and present a comprehensive survey of operations research methodologies that have been applied over the last several decades. The literature review is classified into four main categories: mine design; mine production; mine transportation; and mine evaluation. Mining design models are further separated according to two main mining methods: open-pit and underground. Moreover, mine production models are subcategorised into two groups: ore mining and coal mining. Mine transportation models are further partitioned in accordance with fleet management, truck haulage and train scheduling. Mine evaluation models are further subdivided into four clusters in terms of mining method selection, quality control, financial risks and environmental protection. The main characteristics of four Australian commercial mining software are addressed and compared. This paper bridges the gaps in the literature and motivates researchers to develop more applicable, realistic and comprehensive operations research models and solution techniques that are directly linked with mining industries.
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Sound Thinking provides techniques and approaches to critically listen, think, talk and write about music you hear or make. It provides tips on making music and it encourages regular and deep thinking about music activities, which helps build a musical dialog that leads to deeper understanding.
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It is a big challenge to acquire correct user profiles for personalized text classification since users may be unsure in providing their interests. Traditional approaches to user profiling adopt machine learning (ML) to automatically discover classification knowledge from explicit user feedback in describing personal interests. However, the accuracy of ML-based methods cannot be significantly improved in many cases due to the term independence assumption and uncertainties associated with them. This paper presents a novel relevance feedback approach for personalized text classification. It basically applies data mining to discover knowledge from relevant and non-relevant text and constraints specific knowledge by reasoning rules to eliminate some conflicting information. We also developed a Dempster-Shafer (DS) approach as the means to utilise the specific knowledge to build high-quality data models for classification. The experimental results conducted on Reuters Corpus Volume 1 and TREC topics support that the proposed technique achieves encouraging performance in comparing with the state-of-the-art relevance feedback models.
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In 2001 China amended its copyright law in accordance with the requirements of the Agreement on Trade Related Aspects of Intellectual Property (TRIPS). This thesis explores the impact of copyright reform on China’s domestic film and music industries. Through extensive interviews with film and music industry workers – directors, producers, executives, judges, lawyers and musicians – it investigates the role of copyright in film and music’s shift from state driven to commercially focussed. The construction and negotiation of a new ‘copyright culture’ in China is examined through the lens of Yurchak’s (1999) concept of ‘entrepreneurial governmentality.’ Administrative structures put in place prior to China’s economic reform are no longer capable of controlling film and music production and consumption and new approaches to managing it are becoming more important. High levels of unauthorised distribution are forcing these industries to adapt their business models so that they can function in a system with weak copyright protection. Legal, economic and political changes have resulted in the emergence of an ‘entrepreneurial governmentality’ among film and music industry professionals. This commercially focussed group is, in turn, increasing pressure on the state to expand the space in which it can function and support efforts to strengthen the copyright system that allows it to exist. It is suggested that the construction and negotiation of a new ‘copyright culture’ is now taking place. This thesis describes the current situation in the film and music industries. It examines the tension between the theoretical possibilities created by copyright law, and the practical challenges of operating in China. It observes innovative business models being applied by film and music businesses in China. It discusses the impact of traditional attitudes to copying and also examines the role that open licensing models might play in helping limit the negative effects of copyright protection on public access to content and in raising levels of education about copyright among key groups within the community.
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Inspection of solder joints has been a critical process in the electronic manufacturing industry to reduce manufacturing cost, improve yield, and ensure project quality and reliability. This paper proposes the use of the Log-Gabor filter bank, Discrete Wavelet Transform and Discrete Cosine Transform for feature extraction of solder joint images on Printed Circuit Boards (PCBs). A distance based on the Mahalanobis Cosine metric is also presented for classification of five different types of solder joints. From the experimental results, this methodology achieved high accuracy and a well generalised performance. This can be an effective method to reduce cost and improve quality in the production of PCBs in the manufacturing industry.
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Large margin learning approaches, such as support vector machines (SVM), have been successfully applied to numerous classification tasks, especially for automatic facial expression recognition. The risk of such approaches however, is their sensitivity to large margin losses due to the influence from noisy training examples and outliers which is a common problem in the area of affective computing (i.e., manual coding at the frame level is tedious so coarse labels are normally assigned). In this paper, we leverage the relaxation of the parallel-hyperplanes constraint and propose the use of modified correlation filters (MCF). The MCF is similar in spirit to SVMs and correlation filters, but with the key difference of optimizing only a single hyperplane. We demonstrate the superiority of MCF over current techniques on a battery of experiments.