Advancements in technology have facilitated diverse research strategies in ecoacoustics (or acoustic ecology), algorithmic sound recognition, and aesthetic approaches, with significant scientific and technological applications. These developments have opened new avenues for studying the relationship between humans and their environment through sound. Portable ambisonic recorders, capable of capturing sound trajectories in a 360° sphere, have proven valuable for surround sound systems, as they accurately reproduce the acoustic environment’s spatial characteristics. This technology allows for faithful representation of the sound emitter’s unique qualities, movement patterns, and the reverberant properties of the environment. As a result, soundscape research intersects with multiple disciplines, including robotic listening, census strategies, acoustics, and algorithmic classification of fauna. Moreover, soundscape studies have increasingly contributed to environmental conservation efforts by informing strategies to mitigate the impact of human activities on natural ecosystems.
These technological advancements have facilitated the development of diverse strategies and mechanisms, ranging from traditional audio capture techniques to interactive systems that enable communication between humans and other species through sound. In all cases, soundscape studies provide valuable insights into how human activities impact the environment. This includes analyzing the effects of land and air traffic, power lines that generate electromagnetic fields, and other anthropogenic factors. By interpreting such interactions, soundscape research deepens our understanding of ecological disruptions and contributes to the development of strategies for minimizing human-induced environmental disturbances.
Algorithmic recognition plays a crucial role in identifying and classifying bird vocalizations. In ornithology, specialists undergo extensive training to recognize bird species and their songs based on region or mating season–a process that is time-consuming and requires significant expertise. To streamline this task, applications capable of recognizing and categorizing birdsong have been developed, enhancing efficiency and accuracy. The study of soundscapes has further contributed to refining algorithmic recognition strategies for cataloging wildlife within specific environments. A notable example is the Raven software, developed by Cornell University’s Center for Conservation Bioacoustics, which can analyze audio recordings to identify and classify numerous bird species. This technology has proven invaluable for tracking and documenting avian populations across different regions. As these systems continue to evolve, there is significant potential for further advancements, making automated bioacoustic analysis an increasingly powerful tool in ecological research and conservation.
This according to “Paisaje sonoro: Creatividad interdisciplinaria y tecnologías aplicadas para el registro del canto de las aves” [Soundscape: Interdisciplinary creativity and applied technologies for the recording of birdsong] by Pablo Rubio Vargas and Jorge Rodrigo Sigal Sefchovich (ANTEC: Revista peruana de investigación musical 8/2 [2024] 170–183; RILM Abstracts of Music Literature, 2024-13931).
Click the link below to watch a video titled Empowering bioacoustics research in Southeast Asia, which explains efforts at the Center for Conservation Bioacoustics to create biacoustic networks across the region.
https://www.birds.cornell.edu/ccb/empowering-bioacoustics-research-in-southeast-asia/
Related Bibliolore posts:
https://bibliolore.org/2018/05/21/angelic-bird-musicians/
https://bibliolore.org/2014/11/13/afghan-perceptions-of-birdsong/
