1,720,954 research outputs found
L'Arte Di Interazione Musicale: New Musical Possibilities Through Multimodal Techniques
No full textMultimodal communication is an essential aspect of human perception,
facilitating the ability to reason, deduce, and understand meaning. Utilizing
multimodal senses, humans are able to relate to the world in many different
contexts. This dissertation looks at surrounding issues of multimodal
communication as it pertains to human-computer interaction. If humans rely on
multimodality to interact with the world, how can multimodality benefit the ways
in which humans interface with computers? Can multimodality be used to help
the machine understand more about the person operating it and what
associations derive from this type of communication?
This research places multimodality within the domain of musical
performance, a creative field rich with nuanced physical and emotive aspects.
This dissertation asks, what kinds of new sonic collaborations between musicians
and computers are possible through the use of multimodal techniques? Are there
specific performance areas where multimodal analysis and machine learning can
benefit training musicians? In similar ways can multimodal interaction or analysis
support new forms of creative processes?
Applying multimodal techniques to music-computer interaction is a
burgeoning effort. As such the scope of the research is to lay a foundation of
multimodal techniques for the future. In doing so the first work presented is a
software system for capturing synchronous multimodal data streams from nearly
any musical instrument, interface, or sensor system.
This dissertation also presents a variety of multimodal analysis scenarios for
machine learning. This includes automatic performer recognition for both string
and drum instrument players, to demonstrate the significance of multimodal
musical analysis. Training the computer to recognize who is playing an
instrument suggests important information is contained not only within the
acoustic output of a performance, but also in the physical domain. Machine
learning is also used to perform automatic drum-stroke identification; training
the computer to recognize which hand a drummer uses to strike a drum. There
are many applications for drum-stroke identification including more detailed
automatic transcription, interactive training (e.g. computer-assisted rudiment
practice), and enabling efficient analysis of drum performance for metrics
tracking.
Furthermore, this research also presents the use of multimodal techniques in
the context of everyday practice. A practicing musician played a sensoraugmented
instrument and recorded his practice over an extended period of time,
realizing a corpus of metrics and visualizations from his performance. Additional
multimodal metrics are discussed in the research, and demonstrate new types of
performance statistics obtainable from a multimodal approach.
The primary contributions of this work include (1) a new software tool
enabling musicians, researchers, and educators to easily capture multimodal
information from nearly any musical instrument or sensor system; (2)
investigating multimodal machine learning for automatic performer recognition
of both string players and percussionists; (3) multimodal machine learning for
automatic drum-stroke identification; (4a) applying multimodal techniques to
musical pedagogy and training scenarios; (4b) investigating novel multimodal
metrics; (5) lastly this research investigates the possibilities, affordances, and
design considerations of multimodal musicianship both in the acoustic domain,
as well as in other musical interface scenarios. This work provides a foundation
from which engaging musical-computer interactions can occur in the future,
benefitting from the unique nuances of multimodal techniques
L'arte di interazione musicale : new musical possibilities through multimodal techniques : a dissertation submitted to the Victoria University of Wellington and Massey University in fulfillment of the requirements for the degree of Doctor of Philosophy in Sonic Arts, New Zealand School of Music
No full textMultimodal communication is an essential aspect of human perception,
facilitating the ability to reason, deduce, and understand meaning. Utilizing
multimodal senses, humans are able to relate to the world in many different
contexts. This dissertation looks at surrounding issues of multimodal
communication as it pertains to human-computer interaction. If humans rely on
multimodality to interact with the world, how can multimodality benefit the ways
in which humans interface with computers? Can multimodality be used to help
the machine understand more about the person operating it and what
associations derive from this type of communication?
This research places multimodality within the domain of musical
performance, a creative field rich with nuanced physical and emotive aspects.
This dissertation asks, what kinds of new sonic collaborations between musicians
and computers are possible through the use of multimodal techniques? Are there
specific performance areas where multimodal analysis and machine learning can
benefit training musicians? In similar ways can multimodal interaction or analysis
support new forms of creative processes?
Applying multimodal techniques to music-computer interaction is a
burgeoning effort. As such the scope of the research is to lay a foundation of
multimodal techniques for the future. In doing so the first work presented is a
software system for capturing synchronous multimodal data streams from nearly
any musical instrument, interface, or sensor system.
This dissertation also presents a variety of multimodal analysis scenarios for
machine learning. This includes automatic performer recognition for both string
and drum instrument players, to demonstrate the significance of multimodal
musical analysis. Training the computer to recognize who is playing an
instrument suggests important information is contained not only within the
acoustic output of a performance, but also in the physical domain. Machine
learning is also used to perform automatic drum-stroke identification; training
the computer to recognize which hand a drummer uses to strike a drum. There
are many applications for drum-stroke identification including more detailed
automatic transcription, interactive training (e.g. computer-assisted rudiment
practice), and enabling efficient analysis of drum performance for metrics
tracking.
Furthermore, this research also presents the use of multimodal techniques in
the context of everyday practice. A practicing musician played a sensoraugmented
instrument and recorded his practice over an extended period of time,
realizing a corpus of metrics and visualizations from his performance. Additional
multimodal metrics are discussed in the research, and demonstrate new types of
performance statistics obtainable from a multimodal approach.
The primary contributions of this work include (1) a new software tool
enabling musicians, researchers, and educators to easily capture multimodal
information from nearly any musical instrument or sensor system; (2)
investigating multimodal machine learning for automatic performer recognition
of both string players and percussionists; (3) multimodal machine learning for
automatic drum-stroke identification; (4a) applying multimodal techniques to
musical pedagogy and training scenarios; (4b) investigating novel multimodal
metrics; (5) lastly this research investigates the possibilities, affordances, and
design considerations of multimodal musicianship both in the acoustic domain,
as well as in other musical interface scenarios. This work provides a foundation
from which engaging musical-computer interactions can occur in the future,
benefitting from the unique nuances of multimodal techniques
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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