Toward the Extraction of Ecologically-Meaningful Soundscape Objects: A New Direction for Soundscape Ecology and Rapid Acoustic Biodiversity Assessment?

Intl Workshop on Big Data Sciences for Bioacoustic Environmental Survey
Efficient methods of biodiversity assessment and monitoring are central to ecological research and crucial in conservation management; technological advances in remote acoustic sensing inspire new approaches. In line with the emerging field of Soundscape Ecology, the acoustic approach is based on the rationale that the ecological processes occurring within a landscape are tightly linked to and reflected in the high-level structure of the patterns of sounds emanating from those landscapes ¿ the soundscape. Rather than attempting to recognise species- specific calls, either manually or automatically, analysis of the high level structure of the soundscape tackles the problem of diversity assessment at the community (rather than species) level. Preliminary work has attempted to make a case for community-level acoustic indices. Existing indices provide simple statistical summaries (e.g. Shannon entropy calculated on frequency or time domain signal). In doing so structural complexities arising from spectro-temporal partitioning are lost, limiting their power both as monitoring and investigative tools. In this paper we consider sparse-coding and source separation algorithms for a means to access and summarise ecologically-meaningful sound objects. In doing so we highlight a potentially fruitful union of the conceptual framework of Soundscape Ecology and source separation methods as a new direction for understanding and assessing ecologically relevant interactions in the soundscape.