The Experts below are selected from a list of 15066 Experts worldwide ranked by ideXlab platform
Kevin R Page - One of the best experts on this subject based on the ideXlab platform.
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publishing Musicology using multimedia digital libraries creating interactive articles through a framework for linked data and mei
ACM international conference on Digital libraries, 2018Co-Authors: David Lewis, David M Weigl, Joanna Bullivant, Kevin R PageAbstract:Modern web publishing enables sophisticated presentation of academic arguments, deploying evidence in different formats, using multiple media types, and through interactive user experiences. However, these developments have had little significant effect on the communication of Musicology, which largely continues to be published in static and linear forms, and rarely with user interfaces that connect the different forms of supporting material. Our Music Encoding and Linked Data (MELD) framework uses RDF to associate music-related materials via structures afforded by the Music Encoding Initiative (MEI). Here we describe the use of MELD for publishing multimedia Musicology articles as web applications in which musically-meaningful relationships are mapped to the interactions a user experiences when moving between digital resources such as text, audio, video, and notation. We motivate our work with an enhanced interactive article studying the performance of works by Frederick Delius, and demonstrate our framework's suitability for this situation by implementing a MELD application integrating TEI text, IIIF-served images, MEI notation and recordings of audio and video. We describe the semantic annotations which underpin this realisation, and how they relate the user experience of moving between this content to the musicological argument being marshalled. Through this example we illustrate how connecting diverse media types using musically-meaningful semantics can support a richer form of publication, beyond the current state of the art.
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proceedings of the 3rd international workshop on digital libraries for Musicology
DLfM 2016 3rd International Digital Libraries for Musicology workshop, 2016Co-Authors: Ben Fields, Kevin R PageAbstract:Many Digital Libraries have long offered facilities to provide multimedia content, including music. However there is now an ever more urgent need to specifically support the distinct multiple forms of music, the links between them, and the surrounding scholarly context, as required by the transformed and extended methods being applied to Musicology and the wider Digital Humanities.
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proceedings of the 2nd international workshop on digital libraries for Musicology
DLfM '15 2nd International Workshop on Digital Libraries for Musicology, 2015Co-Authors: Ben Fields, Kevin R PageAbstract:Welcome to DLfM 2015, the 2nd International Workshop on Digital Libraries for Musicology. Many Digital Libraries have long offered facilities to provide multimedia content, including music. However there is now an ever more urgent need to specifically support the distinct multiple forms of music, the links between them, and the surrounding scholarly context, as required by the transformed and extended methods being applied to Musicology and the wider Digital Humanities. The Digital Libraries for Musicology (DLfM) workshop presents a venue specifically for those working on, and with, Digital Library systems and content in the domain of music and Musicology. This includes Music Digital Library systems, their application and use in Musicology, technologies for enhanced access and organisation of musics in Digital Libraries, bibliographic and metadata for music, intersections with music Linked Data, and the challenges of working with the multiple representations of music across largescale digital collections such as the Internet Archive and HathiTrust. DLfM will focus on the implications of music on Digital Libraries and Digital Libraries research when pushing the boundaries of contemporary Musicology, including the application of techniques as reported in more technologically oriented fora such as ISMIR and ICMC. This will be the second edition of DLfM following a very successful and well received workshop at Digital Libraries 2014, giving an opportunity for the community to present and discuss developments in the last year that tackle the agenda that emerged in London. In particular we encourage participants to consider the theme of the main conference - "Large, Dynamic and Ubiquitous" - and how this properties are reflected in Music Digital Libraries and their application to Musicology. We thank you for your contribution, and hope you enjoy what we are sure will be a lively and stimulating discussion!
Peter Organisciak - One of the best experts on this subject based on the ideXlab platform.
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the hathitrust digital library s potential for Musicology research
International Journal on Digital Libraries, 2020Co-Authors: Stephen J Downie, Sayan Bhattacharyya, Francesca Giannetti, Eleanor Dickson Koehl, Peter OrganisciakAbstract:The HathiTrust Digital Library (HTDL) is one of the largest digital libraries in the world, containing seventeen million volumes from the collections of major academic and research libraries. In this paper, we discuss the HTDL’s potential for Musicology research by providing a bibliometric analysis of the collection as a whole, and of the music materials in particular. A series of case studies illustrates the kinds of musicological research that may be conducted using the HTDL. We highlight several opportunities for improvement and discuss promising future directions for new knowledge creation through the processing and analysis of large amounts of retrospective data. The HTDL presents significant new opportunities to the study of music that will continue to expand as data, metadata and collection enhancements are introduced.
Catherine J Stevens - One of the best experts on this subject based on the ideXlab platform.
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music perception and cognition a review of recent cross cultural research
Topics in Cognitive Science, 2012Co-Authors: Catherine J StevensAbstract:Experimental investigations of cross-cultural music perception and cognition reported during the past decade are described. As globalization and Western music homogenize the world musical environment, it is imperative that diverse music and musical contexts are documented. Processes of music perception include grouping and segmentation, statistical learning and sensitivity to tonal and temporal hierarchies, and the development of tonal and temporal expectations. The interplay of auditory, visual, and motor modalities is discussed in light of synchronization and the way music moves via emotional response. Further research is needed to test deep-rooted psychological assumptions about music cognition with diverse materials and groups in dynamic contexts. Although empirical Musicology provides keystones to unlock musical structures and organization, the psychological reality of those theorized structures for listeners and performers, and the broader implications for theories of music perception and cognition, awaits investigation.
Eenjun Hwang - One of the best experts on this subject based on the ideXlab platform.
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smers music emotion recognition using support vector regression
International Symposium Conference on Music Information Retrieval, 2009Co-Authors: Byeong-jun Han, Seungmin Rho, Roger B Dannenberg, Eenjun HwangAbstract:Music emotion plays an important role in music retrieval, mood detection and other music-related applications. Many issues for music emotion recognition have been addressed by different disciplines such as physiology, psychology, cognitive science and Musicology. We present a support vector regression (SVR) based music emotion recognition system. The recognition process consists of three steps: (i) seven distinct features are ex- tracted from music; (ii) those features are mapped into eleven emotion categories on Thayer's two-dimensional emotion model; (iii) two regression functions are trained using SVR and then arousal and valence values are pre- dicted. We have tested our SVR-based emotion classifier in both Cartesian and polar coordinate system empirically. The result indicates the SVR classifier in the polar repre- sentation produces satisfactory result which reaches 94.55% accuracy superior to the SVR (in Cartesian) and other machine learning classification algorithms such as
Mathieu Barthet - One of the best experts on this subject based on the ideXlab platform.
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big data for Musicology
Proceedings of the 1st International Workshop on Digital Libraries for Musicology, 2014Co-Authors: Tillman Weyde, Emmanouil Benetos, Daniel Wolff, Simon Dixon, Stephen Cottrell, Jason Dykes, Dan Tidhar, A Kachkaev, Mark D Plumbley, Mathieu BarthetAbstract:Digital music libraries and collections are growing quickly and are increasingly made available for research. We argue that the use of large data collections will enable a better understanding of music performance and music in general, which will benefit areas such as music search and recommendation, music archiving and indexing, music production and education. However, to achieve these goals it is necessary to develop new musicological research methods, to create and adapt the necessary technological infrastructure, and to find ways of working with legal limitations. Most of the necessary basic technologies exist, but they need to be brought together and applied to Musicology. We aim to address these challenges in the Digital Music Lab project, and we feel that with suitable methods and technology Big Music Data can provide new opportunities to Musicology.
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music emotion recognition from content to context based models
Computer Music Modeling and Retrieval, 2012Co-Authors: Mathieu Barthet, Gyorgy Fazekas, Mark SandlerAbstract:The striking ability of music to elicit emotions assures its prominent status in human culture and every day life. Music is often enjoyed and sought for its ability to induce or convey emotions, which may manifest in anything from a slight variation in mood, to changes in our physical condition and actions. Consequently, research on how we might associate musical pieces with emotions and, more generally, how music brings about an emotional response is attracting ever increasing attention. First, this paper provides a thorough review of studies on the relation of music and emotions from different disciplines. We then propose new insights to enhance automated music emotion recognition models using recent results from psychology, Musicology, affective computing, semantic technologies and music information retrieval.
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multidisciplinary perspectives on music emotion recognition implications for content and context based models
2012Co-Authors: Mathieu Barthet, Gyorgy Fazekas, Mark SandlerAbstract:The prominent status of music in human culture and every day life is due in large part to its striking ability to elicit emotions, which may manifest from slight variation in mood to changes in our physical condition and actions. In this paper, we first review state of the art stud- ies on music and emotions from dierent disciplines including psychology, Musicology and music information retrieval. Based on these studies, we then propose new insights to enhance automated music emotion recog- nition models.
