Managing Animal Sounds - Some Challenges and Research Directions

• Daniel Cintra Cugler UNICAMP
• Claudia Bauzer Medeiros UNICAMP
• Luís Felipe Toledo UNICAMP

Resumo

For decades, biologists around the world have recorded animal sounds. As the number of records grows, so does the difficulty to manage them, presenting challenges to save, retrieve, share and manage the sounds. This paper presents our preliminary results concerning management of large volumes of animal sound data. The paper also provides an overview from our prototype, an online environment focused on management of this data. This paper also discusses our case study, concerning more than 1 terabyte of animal recordings from Fonoteca Neotropical ”Jacques Vielliard”, at UNICAMP, Brazil.

Referências

Bardeli, R. (2009). Similarity search in animal sound databases. Multimedia, IEEE Transactions on, 11(1):68–76.

Barrington, L., Chan, A., Turnbull, D., and Lanckriet, G. (2007). Audio information retrieval using semantic similarity. In Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE Int. Conf. on, volume 2, pages II–725–II–728.

Cobos, M. and Lopez, J. (2010). Listen up the present and future of audio signal processing. Potentials, IEEE, 29(4):40–44.

Daltio, J. and Medeiros, C. (2008). Aondê: An ontology web service for interoperability across biodiversity applications. Information Systems, 33(7-8):724–753.

Dickinson, J., Zuckerberg, B., and Bonter, D. (2010). Citizen Science as an Ecological Research Tool: Challenges and Benefits. Annual Review of Ecology, Evolution, and Systematics, 41(1).

Gerhardt, H. and Huber, F. (2002). Acoustic communication in insects and anurans: common problems and diverse solutions. University of Chicago Press.

Gorder, P. (2006). Not just for the birds: archiving massive data sets. Computing in Science Engineering, 8(3):3–7.

Gunasekaran, S. and Revathy, K. (2010). Content-based classification and retrieval of wild animal sounds using feature selection algorithm. Machine Learning and Computing, Int. Conf. on, 0:272–275.

Uitdenbogerd, A. and Zobel, J. (1999). Melodic matching techniques for large music databases. In Proc. of the 7th ACM Int. Conf. on Multimedia (Part 1), MULTIMEDIA ’99, pages 57–66, New York, NY, USA. ACM.

Weihs, C., Ligges, U., Morchen, F., and Mullensiefen, D. (2007). Classification in music research. Advances in Data Analysis and Classification, 1(3):255–291.

Wells, K. (2007). The ecology & behavior of amphibians. University of Chicago Press.

Wimmer, J., Towsey, M., Planitz, B., Roe, P., and Williamson, I. (2010). Scaling Acoustic Data Analysis through Collaboration and Automation. In 2010 IEEE 6th Int. Conf. on e-Science, pages 308–315. IEEE.