Year: 2026
Type: article
Abstract: This paper presents Identifrog, a mobile citizen science platform fostering ecological listening through frog call recognition. Unlike conventional tools oriented towards definitive classification, Identifrog foregrounds embodied interaction and interpretive openness, embracing ambiguity as part of ecological learning. Using RtD, the system integrates probabilistic AI and interactive spectrograms, framing listening as an active ecological and ethical practice. Drawing on engagements with diverse participants across Taiwan, we show how Identifrog extends thick mapping from visual to sonic modalities. Unlike visual thick mapping’s accumulation of heterogeneous data layers, sonic thick mapping cultivates relational density through temporal deepening, comparative listening, and situated acoustic attunement. Community learning emerges not through public archives but through repeated field encounters that enable novices to refine perceptual judgement. Rather than resolving uncertainty, the platform deploys a design lure strategy and cultivates productive hesitation, inviting users to dwell within sonic ambiguity as a site of ecological inquiry. Through this process, they co-construct ecological meaning and begin to reorient environmental sensing from extraction towards relational learning. We contribute a theoretical articulation of sonic thick mapping and show how an interface positioning AI as a co-listener can support more-than-human forms of citizen science shaped by local context and perceptual sensitivity.
Source: CoDesign
Authors: Yen-Fu Chen, Szu-Ju Wu, Tai-Yuan Su
Institutions: Tatung University, Yuan Ze University
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7211914957