Details

Autor(en) / Beteiligte

• Shufei Duan
• Towsey, M.
• Jinglan Zhang
• Truskinger, A.
• Wimmer, J.
• Roe, P.

Titel

Acoustic component detection for automatic species recognition in environmental monitoring

Ist Teil von

• 2011 Seventh International Conference on Intelligent Sensors, Sensor Networks and Information Processing, 2011, p.514-519

Ort / Verlag

IEEE

Erscheinungsjahr

2011

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• Automatic species recognition plays an important role in assisting ecologists to monitor the environment. One critical issue in this research area is that software developers need prior knowledge of specific targets people are interested in to build templates for these targets. This paper proposes a novel approach for automatic species recognition based on generic knowledge about acoustic events to detect species. Acoustic component detection is the most critical and fundamental part of this proposed approach. This paper gives clear definitions of acoustic components and presents three clustering algorithms for detecting four acoustic components in sound recordings; whistles, clicks, slurs, and blocks. The experiment result demonstrates that these acoustic component recognisers have achieved high precision and recall rate.