Ed Baker FLS ARCS

Picture of Ed Baker.

I am an interdisciplinary researcher investigating how technology can be used to monitor biodiversity, in particular using bioacoustic and ecoacoustic approaches.

GitHub Profile | CV | Media

Latest publications

Good practice guidelines for long-term ecoacoustic monitoring in the UK

Google Scholar

Talks

03/2024 - Next generation monitoring at the Natural History Museum

11/2023 - Garden Science workshop

10/2023 - IBAC 2023

09/2023 - RSPB/Kelvingrove Museum

05/2023 - British Naturalists' Association

All talks

Notes

Prophalangopsis obscura

Linux audio recipes

Acoustics figures

All notes

Some thoughts on:

FlyTunes

FlyTunes is a crowd-sourcing project on the Zooniverse platform to tag short clips of soundscape audio with their contents. These clips are taken from urban settings and will be used to train machine learning models to identify different types of sounds in environments with relatively high levels of anthropogenic noise.

FlyTunes banner

Sample audio file from FlyTunes.

About FlyTunes

Humans are noisy. In cities and towns, our cars, trains, planes, footsteps, and voices all add up to a constant hum of noise and activity. Amidst this human-made soundtrack lies a concealed world of natural sounds - the calls of insects, birds, and other wildlife.

Researchers at the Natural History Museum aim to use recordings from roadsides across the UK to monitor biodiversity and study the impact of road noise on wildlife. As part of the Museum’s Urban Nature Project, community scientists contribute by collecting five-minute audio clips through the Nature Overheard survey.

Join us to unveil the hidden soundscape by listening to short excerpts of these recordings. Your task is to identify the subtle sounds of vehicle hums, human-made sounds and animal chatter within the ambient noise. The background noise will be difficult to categorise, and there will be instances where there are no other distinct sounds. This emphasises the need for a collective effort from the Zooniverse community to carefully work through the files and uncover the hidden sounds.

No need to distinguish between similar sounds - we’ll give you categories. You can listen to each clip multiple times, select multiple options, or admit when the sound stumps you. Each clip gets reviewed by multiple listeners. Join in and explore the hidden sounds within the everyday familiar noise!