Acoular: accessible and reproducible sound localization in Python

• Applicant: Professor Dr.-Ing. Ennes Sarradj
• Subject Area: Acoustics
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 528753521

Acoular is an open Python package for the analysis of multichannel signals from microphone arrays that provides algorithms for tasks such as sound source localization, sound field visualization, and advanced data filtering. It is widely used in the acoustic testing community and for related machine learning applications. The proposal aims to extend the user base to related fields such as robotics, ultrasound and hydro-acoustics and also to create a sustainable basis for future community-based development. The following work is foreseen: improve the current continuous integration process with a better test coverage of the code to address both quality assurance and reproducibility of results, refactor some sub-modules to enable new use cases and interfacing with other research software, develop more strict release and deprecation strategies as well contribution guidelines, extend the documentation with much more worked examples and benchmark data sets and extend training for potential users.

• DFG Programme: Research Grants