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CA3: collaborative annotation of audio in academia
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Source ACM Southeast Regional Conference archive
Proceedings of the 45th annual southeast regional conference table of contents
Winston-Salem, North Carolina
SESSION: Papers table of contents
Pages: 461 - 466  
Year of Publication: 2007
ISBN:978-1-59593-629-5
Authors
Ben Congleton  Virginia Tech, Blacksburg, VA
John Booker  Virginia Tech, Blacksburg, VA
Laurian C. Vega  Virginia Tech, Blacksburg, VA
Meg Kurdziolek  Virginia Tech, Blacksburg, VA
Lauren Shupp  Virginia Tech, Blacksburg, VA
Manuel A. Pérez-Quiñones  Virginia Tech, Blacksburg, VA
Sponsor
SIGAPP: ACM Special Interest Group on Applied Computing
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 5,   Downloads (12 Months): 18,   Citation Count: 1
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ABSTRACT

We present a collaborative tagging tool for audio streams. We discuss two case studies using this tool: The first case study demonstrates the usefulness of simple tags as metadata. The second case study elaborates issues discovered while allowing students to tag events during a classroom lecture, and methods for aggregating and displaying the collected tags. We conclude with insights into collaborative tagging for data retrieval in content streams.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Ellis, D. P., Features for segmenting and classifying long-duration recordings of "personal" audio. In Proc. ISCA Tutorial and Research Workshop on Statistical and Perceptual Audio Processing SAPA-04 Jeju, Korea, 2004.
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Golder, S. and B. Huberman, The Structure of Collaborative Tagging Systems. 2005.
 
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Grabe, M. and K. Christopherson, Evaluating the advantages and disadvantages of providing lecture notes: The role of internet technology as a delivery system and research tool. The Internet and Higher Education, 2005. <b>8</b>(4): p. 291--298.
 
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Lu, L. and H. Zhang, Content analysis for audio classification and segmentation. IEEE Transactions on Speech and Audio Processing, 2002. <b>10</b>(7).
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Vemuri, S., et al., An audio-based personal memory aid. Proceedings of Ubicomp 2004: Ubiquitous Computing., 2004: p. 400--417.
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Collaborative Colleagues:
Ben Congleton: colleagues
John Booker: colleagues
Laurian C. Vega: colleagues
Meg Kurdziolek: colleagues
Lauren Shupp: colleagues
Manuel A. Pérez-Quiñones: colleagues