Bioacoustic Geolocation: Species Sounds as Geographic Signals

Mustafa Chasmai, Wuao Liu, Subhransu Maji, Grant Van Horn

Keywords: bioacoustics, geolocation, audio, iNaturalist, contrastive learning, multimodal retrieval

TL;DR: We hypothesize that bioacoustic signals contain informative geolocation cues and investigate audio geolocation with wildlife sounds.

Abstract: Can we determine someone’s geographic location solely from the sounds they hear? Are acoustic signals enough to localize within a country, state, or even city? We tackle the challenge of global-scale audio geolocation, formalizing the problem, and conducting an in-depth analysis with wildlife audio from the iNatSounds dataset. We hypothesize that bioacoustic signals contain informative geolocation cues because of well-defined geographic ranges of species. To test this, we benchmark image geolocation and soundscape mapping methods on iNatSounds. Building on these insights, we propose a hybrid approach that combines species range prediction with retrieval-based geolocation. We further ask whether geolocation improves with species-diverse recordings and spatiotemporal aggregation across neighboring samples. Finally, we extend our study to multimodal geolocation with case studies from movies that combine both audio and visual content. Our results highlight the potential of incorporating bioacoustic signals into geospatial tasks, motivating future work on species recognition and audio geolocation.

Primary Area: applications to computer vision, audio, language, and other modalities

Submission Number: 6622