TY - GEN
T1 - Chants and orcas
T2 - 2nd ACM Workshop on the Many Faces of Multimedia Semantics, MS 2008
AU - Ness, Steven R.
AU - Wright, Matthew
AU - Tzanetakis, George
AU - Martins, L. Gustavo
N1 - Publisher Copyright:
© Copyright 2008 ACM.
Copyright:
Copyright 2015 Elsevier B.V., All rights reserved.
PY - 2008/10/31
Y1 - 2008/10/31
N2 - The recent explosion of web-based collaborative applications in business and social media sites demonstrated the power of collaborative internet scale software. This includes the ability to access huge datasets, the ability to quickly update software, and the ability to let people around the world collaborate seamlessly. Multimedia learning techniques have the potential to make unstructured multimedia data accessible, reusable, searchable, and manageable. We present two different web-based collaborative projects: Cantillion, and the Orchive. Cantillion enables ethnomusicology scholars to listen and view data relating to chants from a variety of traditions, letting them view and interact with various pitch contour representations of the chant. The Orchive is a project to digitize over 20,000 hours of Orcinus orca (killer whale) vocalizations, recorded over a period of approximately 35 years, and provide tools to assist their study. The developed tools utilize ideas and techniques that are similar to the ones used in general multimedia domains such as sports video or news. However, their niche nature has presented us with special challenges as well as opportunities. Unlike more traditional domains where there are clearly defined objectives one of the biggest challenges has been the desire to support researchers to formulate questions and problems related to the data even when there is no clearly defined objective.
AB - The recent explosion of web-based collaborative applications in business and social media sites demonstrated the power of collaborative internet scale software. This includes the ability to access huge datasets, the ability to quickly update software, and the ability to let people around the world collaborate seamlessly. Multimedia learning techniques have the potential to make unstructured multimedia data accessible, reusable, searchable, and manageable. We present two different web-based collaborative projects: Cantillion, and the Orchive. Cantillion enables ethnomusicology scholars to listen and view data relating to chants from a variety of traditions, letting them view and interact with various pitch contour representations of the chant. The Orchive is a project to digitize over 20,000 hours of Orcinus orca (killer whale) vocalizations, recorded over a period of approximately 35 years, and provide tools to assist their study. The developed tools utilize ideas and techniques that are similar to the ones used in general multimedia domains such as sports video or news. However, their niche nature has presented us with special challenges as well as opportunities. Unlike more traditional domains where there are clearly defined objectives one of the biggest challenges has been the desire to support researchers to formulate questions and problems related to the data even when there is no clearly defined objective.
KW - Audio feature extraction
KW - Machine learning
KW - Multimedia analysis
KW - Multimedia annotation
KW - Semi-automatic annotation
UR - http://www.scopus.com/inward/record.url?scp=84055173841&partnerID=8YFLogxK
U2 - 10.1145/1460676.1460680
DO - 10.1145/1460676.1460680
M3 - Conference contribution
AN - SCOPUS:84055173841
T3 - MM 2008 - Proceedings of the 2008 ACM International Conference on Multimedia, with Co-located Symposium and Workshops: MS 2008
SP - 9
EP - 16
BT - MM 2008 - Proceedings of the 2008 ACM International Conference on Multimedia, with Co-located Symposium and Workshops
PB - Association for Computing Machinery, Inc
Y2 - 31 October 2008 through 31 October 2008
ER -