Interspecies Translation Technologies: Designing Interpretation Interfaces Referencing Simple to Poetically Complex Semiotic Frameworks

This article develops speculative approaches to animal signal interpretation, using artistic methods for engaging and transcoding zoosemiotic qualities of audible animal signals within the design of artificially intelligent (AI) listening devices. The results are experimental translation interfaces that use audio machine learning models, where users can see poetic translations of species’ vocalizations as they occur. The author argues that experimental transcoding of semiotic techniques is a compelling way to present animal signal data to a human audience, and, further, that animal signal interpretation potentially requires the building of poetic overinterpretations that allow species to be seen as minded, and their signals to be seen as compelling to the public.