Content-aware visualizations of audio data in diverse contexts

The visualization of the high-dimensional feature landscapes that are encountered when analyzing audio data is a challenging problem and is the focus of much research in the field of Music Information Retrieval. Typical feature sets extracted from sound have anywhere from dozens to hundreds of dimen...

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Bibliographic Details
Main Author: Ness, Steven
Other Authors: Tzanetakis, George
Format: Thesis
Language:English
Published: 2009
Subjects:
music information retrieval
content-aware visualizations
UVic Subject Index::Sciences and Engineering::Applied Sciences::Computer science
Killer Whale
Orca
Orcinus orca
Killer whale
Online Access:http://hdl.handle.net/1828/2003
id ftuvicpubl:oai:dspace.library.uvic.ca:1828/2003
record_format openpolar
spelling ftuvicpubl:oai:dspace.library.uvic.ca:1828/2003 2023-05-15T17:03:35+02:00 Content-aware visualizations of audio data in diverse contexts Ness, Steven Tzanetakis, George 2009 application/pdf http://hdl.handle.net/1828/2003 English en eng http://hdl.handle.net/1828/2003 Steven R. Ness, Daniel Peter Biro and George Tzanetakis Computer-assisted cantillation and chant research using content-aware web visualization tools, Multimedia Tools and Applications, Accepted for publication. S. R. Ness, A. Theocharis, G. Tzanetakis, L. G. Martins Improving Automatic Music Tag Annotation Using Stacked Generalization Of Probabilistic SVM Outputs, ACM Multimedia 2009. Steven R. Ness, George Tzanetakis, Audioscapes: exploring surface interfaces for music exploration - ICMC 2009. Steven R. Ness, George Tzanetakis, SOMba : Multiuser music creation using Self-Organizing Maps and motion tracking - ICMC 2009. Steven R. Ness, Daniel Peter Biro, George Tzanetakis : Content-aware web browsing and visualization tools for cantillation and chant research, 7th International Workshop on Content-Based Multimedia Indexing. George Tzanetakis, Manjinder Singh Benning, Steven R. Ness, Darren Minifie, Nigel Livingston : Assistive Music Browsing using Self-Organizing Maps - PETRA 2009 : 2nd International Conference on PErvasive Technologies Related to Assistive Environments. Steven R. Ness, Matthew Wright, Luis Gustavo Martins, George Tzanetakis: Chants and Orcas: semi-automatic tools for audio annotation and analysis in niche domains. ACM Multimedia 2008: 9-16. Daniel Peter Biro, Steven Ness, Matthew Wright, W. Andrew Schloss and George Tzanetakis Decoding the Song: Histogram-Based Paradigmatic and Syntagmatic Analysis of Melodic Formulae in Hungarian Laments, Jewish Torah Trope, Tenth Century Plainchant and Koran Recitation EMUS Expressivity in MUsic and Speech : IRCAM - Institut de Recherche et de Coordination Acoustique/Musique - Paris, France. Available to the World Wide Web music information retrieval content-aware visualizations UVic Subject Index::Sciences and Engineering::Applied Sciences::Computer science Thesis 2009 ftuvicpubl 2022-05-19T06:10:50Z The visualization of the high-dimensional feature landscapes that are encountered when analyzing audio data is a challenging problem and is the focus of much research in the field of Music Information Retrieval. Typical feature sets extracted from sound have anywhere from dozens to hundreds of dimensions and have complex interrelationships between data elements. In this work, we apply various modern techniques for the visualization of audio data to a number of diverse problem domains, including the bioacoustics of Orcinus Orca (killer whale) song, partially annotated chant traditions including Torah recitation and the the analysis of music collections and live DJ sets. We also develop a number of graphical user interfaces to allow users to interact with these visualizations. These interfaces include Flash-enabled web applications, desktop applications, and novel interfaces including the use of the Radiodrum, a three-dimension position sensing musical interface. Thesis Killer Whale Orca Orcinus orca Killer whale University of Victoria (Canada): UVicDSpace
institution Open Polar
collection University of Victoria (Canada): UVicDSpace
op_collection_id ftuvicpubl
language English
topic music information retrieval
content-aware visualizations
UVic Subject Index::Sciences and Engineering::Applied Sciences::Computer science
spellingShingle music information retrieval
content-aware visualizations
UVic Subject Index::Sciences and Engineering::Applied Sciences::Computer science
Ness, Steven
Content-aware visualizations of audio data in diverse contexts
topic_facet music information retrieval
content-aware visualizations
UVic Subject Index::Sciences and Engineering::Applied Sciences::Computer science
description The visualization of the high-dimensional feature landscapes that are encountered when analyzing audio data is a challenging problem and is the focus of much research in the field of Music Information Retrieval. Typical feature sets extracted from sound have anywhere from dozens to hundreds of dimensions and have complex interrelationships between data elements. In this work, we apply various modern techniques for the visualization of audio data to a number of diverse problem domains, including the bioacoustics of Orcinus Orca (killer whale) song, partially annotated chant traditions including Torah recitation and the the analysis of music collections and live DJ sets. We also develop a number of graphical user interfaces to allow users to interact with these visualizations. These interfaces include Flash-enabled web applications, desktop applications, and novel interfaces including the use of the Radiodrum, a three-dimension position sensing musical interface.
author2 Tzanetakis, George
format Thesis
author Ness, Steven
author_facet Ness, Steven
author_sort Ness, Steven
title Content-aware visualizations of audio data in diverse contexts
title_short Content-aware visualizations of audio data in diverse contexts
title_full Content-aware visualizations of audio data in diverse contexts
title_fullStr Content-aware visualizations of audio data in diverse contexts
title_full_unstemmed Content-aware visualizations of audio data in diverse contexts
title_sort content-aware visualizations of audio data in diverse contexts
publishDate 2009
url http://hdl.handle.net/1828/2003
genre Killer Whale
Orca
Orcinus orca
Killer whale
genre_facet Killer Whale
Orca
Orcinus orca
Killer whale
op_relation http://hdl.handle.net/1828/2003
Steven R. Ness, Daniel Peter Biro and George Tzanetakis Computer-assisted cantillation and chant research using content-aware web visualization tools, Multimedia Tools and Applications, Accepted for publication.
S. R. Ness, A. Theocharis, G. Tzanetakis, L. G. Martins Improving Automatic Music Tag Annotation Using Stacked Generalization Of Probabilistic SVM Outputs, ACM Multimedia 2009.
Steven R. Ness, George Tzanetakis, Audioscapes: exploring surface interfaces for music exploration - ICMC 2009.
Steven R. Ness, George Tzanetakis, SOMba : Multiuser music creation using Self-Organizing Maps and motion tracking - ICMC 2009.
Steven R. Ness, Daniel Peter Biro, George Tzanetakis : Content-aware web browsing and visualization tools for cantillation and chant research, 7th International Workshop on Content-Based Multimedia Indexing.
George Tzanetakis, Manjinder Singh Benning, Steven R. Ness, Darren Minifie, Nigel Livingston : Assistive Music Browsing using Self-Organizing Maps - PETRA 2009 : 2nd International Conference on PErvasive Technologies Related to Assistive Environments.
Steven R. Ness, Matthew Wright, Luis Gustavo Martins, George Tzanetakis: Chants and Orcas: semi-automatic tools for audio annotation and analysis in niche domains. ACM Multimedia 2008: 9-16.
Daniel Peter Biro, Steven Ness, Matthew Wright, W. Andrew Schloss and George Tzanetakis Decoding the Song: Histogram-Based Paradigmatic and Syntagmatic Analysis of Melodic Formulae in Hungarian Laments, Jewish Torah Trope, Tenth Century Plainchant and Koran Recitation EMUS Expressivity in MUsic and Speech : IRCAM - Institut de Recherche et de Coordination Acoustique/Musique - Paris, France.
op_rights Available to the World Wide Web
_version_ 1766057483764236288

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