talk · Tuesday 22 September · 09:33–⁠09:45 · SAL A

Soundscape China: Listening to the Sounds of Nature with AI

Congtian Lin · AI for Biodiversity Data

Recording time 55:51–1:11:46Open on Vimeo ↗

Summaries and key moments are machine-produced. Check the recording for the speaker’s exact words.

The short versionSoundscape China is building a nationwide acoustic sensor network, database and AI models, gathering 3.6 million recordings in its first year.

Overview

What this was about

Congtian Lin presented Soundscape China, a national initiative to build a passive acoustic monitoring network, a nature-sound database and AI models, while involving citizen scientists and sound artists. The project tests sound sensors from different companies against standards (4G/5G data transfer, solar power, over 50 days' storage); about 280 devices have been deployed by over 110 participating organisations at more than 260 sites, yielding over 3.6 million records in one year. The platform includes a citizen-science recording app, an annotation tool with volunteers, a localised extension of Audubon Core, and a self-supervised pre-trained spectrogram model for sound event detection and classification, illustrated with bird-call activity patterns at three sites in Shandong Province.

Why it matters. Standardised, large-scale acoustic data and open datasets are prerequisites for training reliable sound-recognition models and for using soundscapes as biodiversity indicators.

Key ideas

In the room

  • Soundscape ecology treats sound diversity as an indicator of biodiversity.
  • Framework: platform of sensors, models and database; services for data sharing, annotation, analysis and model training; audiences in monitoring, sound art and citizen science.
  • Device standards: 4G/5G automatic transfer, solar-powered, >50 days storage, plus plug-in microphones for citizen scientists.
  • About 280 devices, 110+ organisations, 260+ sites.
  • Audubon Core was used as the data standard but extended and localised, e.g. for equipment information.
  • Pre-training on time and frequency patches of spectrograms supports downstream sound event detection and classification.
  • The programme is endorsed by ISSP within the UNESCO science decade.
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Notable moments

In their words

Transcript

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Programme abstract

Soundscape China - Listening to the Sounds of Nature with AI

Congtian Lin

With the rapid advancement of artificial intelligence and acoustic sensing technologies, the use of sound for biodiversity monitoring has evolved from localized experiments to widespread application. The construction of a national intelligent monitoring network based on natural sounds has become a key research direction in the field of ecological monitoring. The "Soundscape China" project is precisely centered on the goal of intelligent natural soundscape monitoring. It addresses multiple critical components-ranging from sensor development and intelligent species identification modeling to the construction of big data platforms-and is dedicated to creating an integrated technological chain that encompasses "acquisition, recognition, and management." The project strives to provide a standardized, replicable, and scalable model for the industry.

To date, Phase I of the "Soundscape China" project has deployed over 120 acoustic monitoring devices nationwide, which have automatically collected and aggregated more than 2 million valid recordings. The monitoring coverage spans diverse ecosystem types, including forests, wetlands, farmlands, grasslands, and deserts, thereby providing robust data support for national biodiversity monitoring. The project has been officially selected for inclusion in the United Nations' "Decade of Science" program. In the future, it aims to further expand the intelligent natural soundscape monitoring network, while also deepening cross-disciplinary practices such as citizen science education and sound art. This will promote multi-disciplinary synergy and foster an innovative framework of positive interaction among technology, ecology, and society.

Submitted to the conference programme before the talk, so the talk itself may differ.