/plushcap/analysis/deepgram/forests-and-machine-learning

Listening to Forests with Machine Learning & Algorithms

What's this blog post about?

Listening to Forests with Machine Learning & Algorithms is a study that explores how bioacoustics and ecoacoustics can help researchers better understand the health of forests and their inhabitants by "listening" to forests at scale. Bioacoustics studies individual organisms' use of sound, while ecoacoustics studies entire ecological “soundscapes.” Both fields often employ passive acoustic monitoring devices, spectrograms, and machine learning algorithms to study organisms' and ecosystems' sounds. The article discusses various applications of these methods, including counting African forest elephants, studying their behavior, and measuring biodiversity in recovering forests. It also highlights the challenges faced by researchers in this field, such as parsing the signal from the noise, developing machine learning models that can run locally on recording devices, and making data analyses intuitive enough for conservation and anti-poaching practitioners to quickly interpret and react to.

Company
Deepgram

Date published
Jan. 26, 2024

Author(s)
Brad Nikkel

Word count
3882

Language
English

Hacker News points
None found.


By Matt Makai. 2021-2024.