I am interested in the sensory aspects of acoustic communication. Which signal properties carry information such as species identity? Which processing steps allow a receiver to extract and read out a signal from a noisy environment? What are functional limitations of this processing, and how do they factor into the evolution of species that depend on acoustic communication? 

Grasshoppers are a suitable model system to adress these questions. They possess a simple and well-researched auditory system, and they produce a variety of characteristic acoustic signals. Therefore, during my master thesis, we developed a physiologically inspired model for the species-specific detection of grasshopper songs. The signal is transformed according to known auditory processing stages and eventually represented in a high-dimensional feature space, in which the songs of a given species form a distinct cluster. I now explore how structure and parameters of the modelled pathway constrain the detectability of different songs. For instance, we've built microphone arrays for recording at multiple distances from the sound source to test the system's ability to compensate for different signal intensities. Besides, I enjoy developing my own Python-based tools but prefer getting in close contact with my chosen model species, and nature in general. To this end, I've started to record from the local Orthoptera species, and maintain a map of observations for several areas near Tübingen.